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August 18, 2026

How FleetHub.AI is Redefining Fleet Intelligence with E.L.L.A.

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Robots & Pencils

A Conversation with FleetHub.AI CEO Marc Lonson

FleetHub.AI has been helping transportation and logistics companies simplify fleet operations through connected technology. By bringing together rugged hardware, wireless connectivity, mobile device management (MDM), and mobility solutions into a single ecosystem, FleetHub.AI has focused on one mission: making it easier for fleets to stay connected, productive, and compliant.

Now, the company is taking the next step in that evolution.

Meet E.L.L.A.! FleetHub.AI’s Intelligent Operating Layer. Purpose-built for the transportation industry, E.L.L.A. combines real-time operational data with agentic AI to proactively support drivers, fleet managers, and operations teams. Rather than adding another dashboard or chatbot, E.L.L.A. works behind the scenes, delivering the right information at the right time to help fleets operate more efficiently.

We sat down with FleetHub.AI CEO Marc Lonson, and our own Scott Young to discuss the inspiration behind E.L.L.A., how it builds on FleetHub.AI’s long-term vision, and why intelligent fleet operations are about empowering people, not replacing them.

Question: What inspired you to create E.L.L.A., and why now?

Marc Lonson, CEO Fleethub.AI: FleetHub.AI has always been focused on solving real-world challenges for transportation companies. Every solution we’ve developed has been driven by one question: How can we make life easier for the people who keep freight moving?

I’ve spent many years working alongside fleets and have developed an incredible appreciation for professional drivers. They’re the backbone of our economy, yet they’re expected to navigate increasingly complex technology, regulations, and day-to-day operational demands.

E.L.L.A. grew out of that understanding.

The timing couldn’t be better. Artificial intelligence has matured to the point where it can provide meaningful, contextual assistance, not just answer questions. Combined with the connected platform we’ve built at FleetHub.AI, we now have the ability to proactively support drivers and fleet teams in ways that simply weren’t possible a few years ago.

For us, E.L.L.A. isn’t about introducing AI for the sake of AI. It’s about making every interaction with technology simpler, smarter, and more valuable.

Question: Everyone seems to be adding AI to their products. How is E.L.L.A. different?

Marc Lonson: AI has become a buzzword, and it’s easy to understand why. But simply adding AI doesn’t automatically create value.

What makes E.L.L.A. different is the context.

Because she’s built into the FleetHub.AI ecosystem, E.L.L.A. understands the operational environment she’s working in. Through secure APIs and webhook integrations, she consumes data that’s directly relevant to each fleet, each driver, and each workflow.

That means she isn’t providing generic answers. She’s delivering proactive, real-time guidance that’s specific to what’s happening in that moment.

Whether it’s helping with Hours of Service, inspection readiness, tablet health, or operational workflows, E.L.L.A. quietly works in the background, stepping in only when she’s needed.

That’s why we describe E.L.L.A. as an Intelligent Operating Layer rather than just another AI application.

Question: How does E.L.L.A. fit into the way fleets already operate today?

Marc Lonson: One of our biggest priorities was making sure customers wouldn’t have to change the way they operate.

FleetHub.AI built a connected mobility ecosystem that brings together hardware, connectivity, device management, and operational technology. E.L.L.A. builds on that foundation.

Because she integrates through existing APIs and webhooks, fleets don’t need to replace their current systems or redesign their workflows. Drivers continue using the tools they’re already familiar with, while E.L.L.A. works behind the scenes, connecting information across the platform and providing proactive guidance when it’s most valuable.

Technology should adapt to the customer, not the other way around.

Question: What are the biggest operational challenges E.L.L.A. is designed to solve for fleet operators?

Marc Lonson: Every fleet faces countless operational decisions every day. Many of them are repetitive, time-consuming, and preventable.

Our goal is to remove as much operational friction as possible by giving people the information they need before they have to ask for it.

Today, E.L.L.A. can help fleets by:

  • Preventing unidentified driving events before manual intervention is required.
  • Providing proactive Hours of Service compliance guidance and parking recommendations.
  • Preparing drivers with inspection briefings before inspections begin.
  • Monitoring tablet health to identify potential issues before they disrupt operations.
  • Delivering an intuitive, context-aware knowledge base that surfaces relevant information exactly when it’s needed.

Individually, those capabilities save time. Together, they reduce administrative workload, improve compliance, minimize downtime, and help drivers stay focused on what matters most, driving safely and efficiently.

Question: How will fleet managers experience E.L.L.A. differently from the software they use today?

Marc Lonson: Traditional software tells you what happened yesterday. E.L.L.A. is designed to help you avoid tomorrow’s problems.

Fleet managers should notice fewer calls back to the office because drivers already have the information they need. They’ll spend less time assigning drive time after unidentified driving events and less time responding to routine operational questions.

Instead of creating another dashboard full of alerts, E.L.L.A. reduces the number of alerts that need attention in the first place.

That’s a fundamentally different experience.

Question: Is E.L.L.A. replacing people or helping them work smarter?

Marc Lonson: That’s an important question because there’s a lot of uncertainty around AI.

The answer is simple; E.L.L.A. isn’t here to replace people.

She’s here to support them.

Think of E.L.L.A. as an intelligent co-pilot that works alongside drivers, dispatchers, safety managers, and fleet operators. She proactively identifies opportunities to help, surfaces relevant information, and reduces repetitive manual tasks so people can focus on higher-value work.

The expertise, judgment, and relationships that make great fleet professionals successful will always come from people. E.L.L.A.’s role is to amplify those strengths.

Question: If fleet operators remember one thing about E.L.L.A., what do you hope it is?

Marc Lonson: I hope they remember why we built her.

Everything starts with the driver.

When drivers have the information they need exactly when they need it, they’re more confident, more productive, and less distracted. That creates a ripple effect across the entire organization.

Safer drivers lead to more efficient operations. More efficient operations lead to better customer service. Better customer service leads to stronger businesses.

If E.L.L.A. improves the driver’s day, everyone benefits.

Question: FleetHub.AI has always focused on simplifying fleet operations. How does E.L.L.A. build on that mission?

Marc Lonson: FleetHub.AI has never been about selling individual products.

We’ve always been focused on building a connected ecosystem for transportation companies.

Our platform brings together rugged hardware, wireless connectivity, mobile device management, and mobility technology into one integrated experience. E.L.L.A. is the intelligence layer that brings all of those capabilities together.

Instead of simply collecting operational data, FleetHub.AI can now help fleets understand that data, anticipate issues, and take action before those issues affect drivers or operations.

That’s where the real value of AI comes from, not replacing existing technology, but making every part of the platform smarter.

Question: What excites you most about what E.L.L.A. will enable for customers over the next few years?

Marc Lonson: This is only the beginning.

One of the things I’m most excited about is learning alongside our customers. As fleets continue using E.L.L.A., we’ll measure the impact she’s having and listen carefully to the challenges they still want solved.

Transportation never stands still, and neither will FleetHub.AI.

We already have exciting ideas for where E.L.L.A. goes next, but we’ll keep those under wraps for now. What’s important is that we’ve built a platform designed to evolve continuously, helping our customers solve today’s problems while preparing them for tomorrow’s opportunities.

Question: From an engineering perspective, what made E.L.L.A. a unique and exciting project to build?

Scott Young: E.L.L.A. sits in a different category from most “add AI to it” products. Most fleet AI tools report to the back office after something already happened. E.L.L.A. had to work the opposite way: catch a problem before it happens, in a cab, with a driver who can’t stop and stare at a screen. That constraint made this fun to build. Voice-first, proactive, event-driven: every decision had to hold up in the real conditions of a moving truck, not a demo environment. Building an agent that acts on its own judgment inside someone’s workday, without asking them to change how they work, is a genuinely hard problem. That’s exactly the kind we like.

E.L.L.A. runs on Amazon Nova 2 Sonic for real-time voice and Amazon Bedrock for reasoning, with AWS Lambda, Amazon API Gateway, and Amazon DynamoDB handling everything in between.

Question: When FleetHub first shared its vision for E.L.L.A., what stood out to your team, and what made you excited to help bring it to life?

Scott Young, EVP of Growth and Strategic Alliances, Robots & Pencils: What stood out from day one was how clearly Marc and Ella understood the real cost of driver friction, drawn from decades spent inside fleet operations, telematics, and device security. They came to us with a clear ask: build a co-pilot that earns a driver’s trust in silence, showing up right when needed and staying out of the way otherwise. That clarity made the partnership work. We knew exactly who we were building for and why it mattered.

Question: Looking back from concept to launch, what are you most proud of, and what makes E.L.L.A. different from other AI solutions entering the market?

Scott Young: What we’re most proud of is that E.L.L.A. was built to work for the driver first, ahead of the back-office dashboard. It acts in the moment: before a violation gets recorded, before hours run out, before an inspection catches a driver off guard. Most AI entering this market is built to inform someone later. E.L.L.A. is built to help someone now, and that timing is the real differentiator.

Looking Ahead…

For FleetHub.AI, E.L.L.A. is more than the company’s latest innovation – it’s the next evolution of its mission to simplify fleet operations through intelligent technology.

By combining connected hardware, wireless connectivity, mobile device management, operational data, and agentic AI into a single ecosystem, FleetHub.AI is redefining how transportation companies interact with technology. Instead of asking drivers and fleet managers to adapt to disconnected systems, the platform works together as one intelligent environment, providing proactive guidance, reducing operational complexity, and empowering people to make better decisions every day.

As the transportation industry continues to evolve, so will FleetHub.AI. And with E.L.L.A. leading the way, the future of fleet intelligence isn’t just connected, it’s proactive, contextual, and built around the people who keep the world moving.

Learn more about Robots & Pencils solutions for transportation and logistics companies.

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How to Run a Marketing Function with Generative and Agentic AI on Amazon Quick 

Adrian Bird & Christina Morello

A conversation with Christina Morello, VP of Marketing
Interviewed by Adrian Bird, VP of AWS Partnership

The Setup: Rebuilding Marketing on Amazon Quick

Q: You run marketing for Robots & Pencils, and, as you know, we are all in on AWS and Generative AI. How has the company influenced the way you have built out the marketing team ?

Marketing for an applied AI engineering partner comes with a built-in hypocrisy risk. If we are out telling enterprise clients to put generative and agentic AI into production, my marketing function cannot be running on willpower and a content calendar in Google Sheets. I would be like a swimming instructor who refuses to get in the pool.

When I joined the team, the first question I asked was how we can design marketing operations the same way we architect solutions for enterprise clients: AI-first, designed around outcomes, scalable without a hiring spree. I also needed a system that could accommodate personal constraints, I have Multiple Sclerosis, and I needed something that would hold up across good days and harder ones.

Amazon Quick turned out to be the answer, and my whole marketing operation lives on the platform now. Custom Agents are my specialist teammates, Spaces hold the knowledge architecture, Quick Research runs the competitive and industry intel, and Flows automate the editorial calendar. I run all of it on my own, and the work still goes out the door before the coffee gets cold.

Q: Can you say more about what you mean by “agents being your teammates”?

Most marketing leaders I talk to right now are doing the work of three people while learning a brand-new tool stack on their lunch break. AI only sharpened that pressure, because now we are also supposed to be experts in a discipline that barely existed a year ago.

My first instinct was the same as everyone else’s: start hiring. And that is more or less what I did by building and executing a hiring plan, just not the kind with headcount attached.

I now have a team that runs 24×7 and never burns out. My AI marketing agents on Quick each fill a specific role: brand strategist, competitive analyst, content specialist, operations manager, industry research analyst, and so on. Each one built for a specific function, fed a curated diet of source material, and held to a tight set of rules, the same as any new hire I would bring onto a real team.

The Architecture: Amazon Quick for Marketing, Layer by Layer

Q: Walk me through how this is structured on Quick.

Custom Agents act as named teammates for specific functions, Spaces hold the curated source material each agent is bound to, Quick Research runs the competitive and industry scans, Flows automate the editorial calendar so the system is driving the cadence, and Chat handles real-time iteration when something has to go live fast.

For example, most marketers will recognize the time sink of brand policing. I ensure every piece of content created clears a four-filter test. The filters themselves are my secret, but I can tell you that before Quick, those filters were a bottleneck. Running them by hand slowed me down and skipping them produced off-brand content. Chasing every off-brand sentence, missed citation, and freelance claim before it lands in front of the world. The most useful thing Quick does is take that off my plate by building it in. My agents only pull from sources I designate, cite only from real documents, and their constrained knowledge prevents fabrication and hallucinations. Which means we publish better, highly relevant content at the speed this industry actually moves, and the brand-policing hours I used to spend on review cycles now go into strategy.

Staying Current

Q: Robots & Pencils operates in a category where the technology itself is changing the story. How do you manage messaging consistency inside that?

Every marketing leader I know is trying to stay on the AI messaging mechanical bull. Capabilities expand, market framing shifts, and messaging changes quarter to quarter, which hits everything we produce: the website, the decks, the sell sheets, the videos, the articles. Minor adjustments are constant just to stay current, and the only thing worse than making them is not making them.

With Quick, my source of truth lives in a Space. When positioning shifts, I update the source, everything downstream reflects it, and a change that used to take weeks across a team turns around much quicker.

The cognitive load of tracking changes across a team disappears too, which matters more than most marketing leaders admit, and matters even more for the ones whose capacity moves around.

The Outcomes

Q: What does this produce in measurable business outcomes?

The numbers for 2026 alone are specific. Our website is running nearly 1.5x above the industry’s top-performing quartile. In the first half of 2026, robotsandpencils.com grew traffic 40% while pulling in a 99% new user rate, meaning the brand is consistently reaching untapped audiences. Organic search hit a 59% engagement rate, which tells you the content is attracting people who are actively looking for enterprise AI solutions. High-value pages are holding 76–79% engagement rates. Most importantly, monthly traffic volume has grown consistently every month, which is evidence of compounding growth, not a one-time spike. And the leads? We have a more than steady stream pouring in.

Robots & Pencils’ LinkedIn page organic follower growth accelerated 1,417%, and monthly impressions saw a 437% jump in just five months. On active posting days, our engagement rate runs more than 4x the industry average and well above the platform-wide median of 5.2%.

The numbers say what they say: this strategy is punching well above its weight.

The Philosophy

Q: What would you tell other functional leaders considering this approach?

When leaders ask me about agentic AI for marketing, I tell them not to start with the tool. Figure out what you want the work to produce and the rules that keep it on track first, if you can do that, picking the tool is the easy part.

My time in education marketing taught me something simple: quality output follows a quality system. The great teachers I have known build the structure, assessment frameworks, feedback loops, and scaling mechanisms. Then they teach inside that structure at a level they could not sustain otherwise.

I think this works for any function, build the environment, and produce inside it. The expertise stays yours, and the AI gives it scale.

Q: You have been candid about this system filling operational gaps. Is any of that personal for you?

I cover upwards of seven industry verticals, a full editorial calendar, enterprise-grade thought leadership, advertising, and AWS-compliant positioning across every touchpoint. It’s a lot, and I have Multiple Sclerosis which is known for cognitive issues, slower processing, and difficulty with multitasking. This system handles the parallel execution. I bring the framework for what needs to get done and 25 years of expertise to govern how it gets done.

For anyone working with a disability, this is the kind of system that lets you keep showing up at full strength when your body has other plans.

Q: Last question. What’s next?

What’s next for me is the work I came into marketing for. Amazon Quick has taken the review cycles, the brand-policing hours, and the parallel execution off my plate. The strategy, the storytelling, and the conversations are where I want to spend my time now.

A new vertical means a new Space and a new specialist teammate, a new workflow gets a Flow or Automation, and when it comes to adding headcount, I have clearer definition of the skills needed, and they are those that only a human can perform.

Marketing is one function, and every team across Robots & Pencils works this way. Engineers and delivery leads operate with their own agentic teammates grounded in their own curated systems of record. Our client-facing teams do the same. We do not recommend this approach to enterprise clients and then sneak back to the old way once everyone has left the room. This is how Robots & Pencils actually works.

One more thing. Marketing leaders working with a disability, chronic illness, neurodivergence, or caregiving responsibilities will recognize the benefit Quick offers here. Anyone running a marketing function gains from it, and some of us notice it sooner. That is the part of agentic AI I am most invested in talking about.

Want to see how Amazon Quick can transform your enterprise workflows? Request an AI Briefing today.

FAQs

Source: Amazon Quick User Guide

What is Amazon Quick?

Amazon Quick is a comprehensive, generative AI-powered business intelligence platform that makes it easy to analyze data, create visualizations, automate workflows, and collaborate across your organization. The service combines traditional business intelligence capabilities with modern AI assistance, requiring no machine learning expertise to use. You can connect to diverse data sources, create interactive dashboards, build intelligent automations, and get immediate insights through natural language conversations with AI agents.

Quick includes five integrated capabilities that work together: Amazon Quick Sight for data visualization, Amazon Quick Flows for workflow automation, Amazon Quick Automate for process optimization, Amazon Quick Index for data discovery, and Amazon Quick Research for comprehensive analysis. The platform extends beyond traditional BI by bringing AI assistance directly into your existing tools through extensions for browsers, Slack, and Microsoft Office applications. You can also build and publish interactive web applications using apps in Amazon Quick.

What is a Space in Amazon Quick?

A space in Amazon Quick is a collection of data and Quick resources scoped for a particular team or domain. You can use spaces to aggregate and organize files, dashboards, topics, knowledge bases, and application actions into a unified and customizable knowledge center for your team. Spaces integrate seamlessly with Quick agents for contextual conversations and are designed to scale across personal, team, and cross-team use cases.

Spaces allow your team to get the most relevant results from conversational agents and other AI tools inside Quick by grounding the results with only data relevant for your task or domain. Multiple people on the team can contribute to the knowledge inside a space; this reduces data silos and streamlines information discovery. Spaces also serve as a data layer for apps in Amazon Quick applications.

What is Amazon Quick Sight?

Amazon Quick Sight is a comprehensive business intelligence service that enables you to transform raw data into meaningful insights through interactive visualizations, dashboards, and reports. Whether you’re connecting to databases, preparing datasets, creating analyses, or sharing dashboards with stakeholders, Amazon Quick Sight provides the tools you need to make data-driven decisions.

What is Amazon Quick Research?

Amazon Quick Research is a feature of Amazon Quick that enables you to conduct comprehensive research by analyzing multiple data sources and generating detailed reports. Quick Research uses artificial intelligence to help you gather, analyze, and synthesize information from various sources including web search, uploaded files, connected data spaces, knowledge bases, actions, and third-party data providers.

With Quick Research, you can define research objectives, select relevant data sources, and receive AI-generated research reports with proper citations and source tracing. This helps you make informed decisions based on comprehensive analysis of available information.

What is Amazon Quick Flows?

Amazon Quick Flows is a capability within Amazon Quick that lets any user create, customize, and share workflows that automate routine tasks. You can generate flows from conversations with chat agents, describe what you need in natural language, or build them manually using the visual editor — no technical skills required. Flows can also be published to an admin-managed library and shared with other Amazon Quick users in your organization.

Each flow is a sequence of steps that can gather user input, generate AI responses from your data or the web, take actions in connected applications, and apply logic to control how steps run.

What is Amazon Quick Automate?

Amazon Quick Automate is an AI-powered application that creates sophisticated automations using natural language or documentation. Amazon Quick Automate revolutionizes enterprise workflow by transforming complex processes into intelligent, adaptive automations.

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Robots & Pencils Hits Three AWS Summits in June with One Message: It’s Time to Launch and Scale AI

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Robots & Pencils

The AWS Advanced Tier Services Partner will meet with enterprise and public sector teams across Los Angeles, New York City, and Washington, D.C.  

AWS releases generative and agentic AI services faster than most enterprises can deploy them, and that gap is widening every quarter they wait. In June, the Applied AI Engineering Partner will be on the ground at three AWS Summit events, ready to sit down with enterprise and public sector leaders who are done with pilots and ready to take generative and agentic AI live.

The AWS Summit series is where enterprise technology leaders gather to see what is possible on AWS. As an AWS Advanced Tier Services Partner and one of 11 inaugural AWS Pattern Partners selected from the AWS Partner Network, Robots & Pencils is the nimble, high-velocity alternative to traditional global systems integrators. Every engagement starts with the outcome the client needs and earns it with evidence. Velocity Pods, Robots & Pencils’ atomic delivery units, are small teams of senior practitioners that take AI solutions from concept to production on Amazon Bedrock and Amazon Bedrock AgentCore in weeks, compared to 6 to 12 months with a traditional systems integrator. 

“AWS has built the full-stack agentic AI infrastructure. The technology is ready. What we do is put it to work fast,” said Adrian Bird, VP of AWS Partnership at Robots & Pencils. “We work with your teams to build the business architecture that takes enterprise AI live before the next board meeting.”

“Enterprises don’t need another aircraft carrier full of consultants in the AI era,” said Jeff Kirk, EVP of Applied AI at Robots & Pencils. “They need a speedboat, a forward deployed team small enough to be surgical, senior enough to build for scale with, and fast enough to prove ROI before the next budget cycle.”

What the Robots & Pencils Builds on AWS 

Agentic AI with AWS is the core of the work. AI agents built on Amazon Bedrock and Amazon Bedrock AgentCore that work alongside human teams in live not in a sandbox. 

Cloud Modernization gets organizations off aging infrastructure and onto a serverless, AWS-native foundation built to scale, not just to run. 

Cloud and AI App Development is where engineers and creatives build in the same room, producing cloud-native applications with generative AI in the architecture from day one. 

For enterprise and public sector teams attending any of the three summits, the Robots & Pencils team is ready to talk. 

Schedule time with the Robots & Pencils team:  

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AWS Summit Warsaw 2026: What We Saw, Who We Met, and What It Confirmed 

Ukraine Team Members

Our Ukraine team spent May 6 at the AWS Summit (EXPO XXI) in Warsaw. Here is what we saw, what surprised us, and what we are bringing back. 

EXPO XXI is a short ride from the center of Warsaw, and on a May morning you can feel the conference before you see it. The queue outside was long but moving fast. Hoodies, lanyards, laptop bags. The crowd skewed more senior than you might expect at a free regional event.  

Our plan was deliberate. Show up early, split the agenda, cover more ground in parallel, regroup over coffee, and most importantly, validate our approach.  

Robots & Pencils team members in attendance, from left to right: Bohdan Popovych, Rostyslav Volskyi, and Stanislav Makar. 

Robots & Pencils team members in attendance, from left to right: Stanislav Makar, Rostyslav Volskyi, and Bohdan Popovych. 

Agentic AI is the AWS Headline. 

The opening keynote made one thing clear. Agentic AI is the organizing thesis for everything AWS is building in 2026. 

Three names anchored the story. Kiro, the agentic IDE that got a fresh push at re:Invent 2025, featured prominently with its spec-driven development model, sequenced task generation, and agents that produce tests alongside code. Nova 2, the model powering more of the AWS AI surface, continues its region-by-region rollout. AWS Transform, their modernization platform for mainframe, VMware, and .NET workloads, framed as the agentic path into enterprise legacy systems. 

Real customer stories on stage. Real numbers. Real screenshots. The European Sovereign Cloud and the EMEA AI Hub got dedicated time, which landed well with the Warsaw audience. The framing was consistent throughout: the shift from AI tools you prompt to AI agents that reason, plan, and act is underway. The question for builders is how you instrument, evaluate, and trust what those agents do. 

That question got a very good answer in the next session. 

The Session That Landed: AgentCore Evaluations in Production 

Right timing matters at a conference, and the AgentCore deep-dive landed at exactly the right moment. AWS spent the spring pushing AgentCore Evaluations hard. It went GA on March 31, 2026, and the Warsaw session put it directly in front of European builders. 

The plain-language version of what it does: a managed service that continuously monitors agent quality against real production traces, not just test suites. You are shipping agents. You need to know they work. Handing someone a scorecard you hand-rolled for each project is not a sustainable answer. This is. 

The built-in evaluators cover what matters in production: 

  • Correctness. Did the agent get the answer right? 
  • Helpfulness. Was the response useful to the person asking? 
  • Tool selection accuracy. Did the agent pick the right tool for the step? 
  • Safety. Did anything in the output violate policy? 
  • Goal success rate. Did the multi-step task complete? 
  • Context relevance. Did the retrieved context match the question? 

On top of those you can configure custom evaluators. LLM-as-judge with your own prompt and model, or code-based evaluators running on Lambda. The same framework handles hallucination detection and JSON schema validation without forcing two different toolchains. 

The detail that made us lean forward: full OpenTelemetry compatibility. The evaluator scores flow into existing dashboards alongside session count, latency, token usage, and error rates. You can alert on agent quality the same way you alert on a CPU spike. 

For anyone building agents on behalf of enterprise customers, this solves the credibility problem. “How do you know it works in production” is no longer a hand-waving moment. 

The Best Conversation Happened at the Espresso Machine 

One of the more useful exchanges of the day started while waiting for coffee. 

AWS set up a cloud-ordered espresso bar on the expo floor. You scanned a QR code, placed your order in a small web app, and the espresso machine queued it. When the drink was ready, the screen showed your name. No line. No barista small talk. Beautifully on-brand for a cloud event, and genuinely better than the alternative. 

Serverless Coffee Bar - AWS Summit Warsaw Robots and Pencils

While we waited, a conversation started with a Senior Solutions Architect at AWS. It turned into one of the most useful exchanges of the day. The topic was whether Lambda is a credible runtime for agentic workflows. The honest answer is: it depends on whether you have state. 

An agent is not a request and a response. It is a long, branching workflow with LLM calls, tool invocations, and occasional human-in-the-loop steps. Lambda durable functions, which AWS shipped in late 2025 and has been shaping for agentic use cases since, address this directly. Each LLM call and each tool invocation becomes a checkpointed step inside a single Lambda. If execution times out mid-loop, the next invocation replays from the last checkpoint and skips completed steps. No Step Functions wiring. No custom state store. No DIY replay logic. The orchestration lives in the function code, in the language you already use. 

The Java SDK went GA in April 2026. Durable functions are now available in sixteen additional regions. 

The Best Hour of the Day: Knowledge Graphs 

Two talks on knowledge graphs stood out as the strongest technical content of the summit. The first was delivered by Dmytro Romantsov, Senior SRE at Miro, on their internal AI agent built over an organizational graph. The talk was technically dense and honest: he walked through what failed before the team settled on a graph-backed architecture, what the graph actually contains, how updates flow into it, and where the approach delivers measurably better results than the pre-graph baseline. 

After the session, we walked over to talk to him. Small-world moment: we share a first language, switched off English immediately, and the conversation opened up. The core thesis from both the talk and the follow-up conversation was consistent. Enterprise AI agents are only as good as the organizational knowledge they can reason over. A graph gives that knowledge structure, updateability, and query depth that flat retrieval cannot match. That is not a new idea, but watching it validated independently at Miro’s scale makes the argument more concrete. 

The second strong graph talk came from an SLB engineer in DEV207, on context graphs for explainable AI agents. The framing that stuck: the difference between a state clock and an event clock. Most pipelines today reflect the current state of a system. A context graph that also captures decision events can answer “why did this happen, and in what order.” That is the kind of explainability enterprise buyers are starting to require as agents move from pilot to live. 

Asking Honest Questions About AWS Transform 

The AWS Transform booth was busy. The team arrived with a direct question about IBM RPG support and walked through the answer methodically with a Solutions Architect for Migration and Modernization at AWS. 

The most telling moment was watching an AWS specialist type the same question into their own tool in front of us. The answer came back: yes, with limitations, followed by pages of caveats. Informative in its own way. 

The bottom line is that AWS Transform is production-grade for COBOL, Java-to-JavaScript migrations, VMware modernization, and mainframe workloads. RPG support is real but not ready for complex production use cases. We left with clarity on where the tool genuinely shines and where the right path is a combination of other tools and hand-rolled pipelines. That kind of honest answer is the second-best outcome at a conference. It tells you your reasoning was sound. 

The VMware migration angle, by contrast, is genuinely strong. Broadcom’s license changes are creating real urgency for customers running on VMware infrastructure. Worth flagging for relevant engagements. 

The Compute Thesis: AWS is Sizing Infrastructure for Self-Managed AI 

A theme ran underneath the agentic-AI headline all day: AWS is provisioning compute to match the shape of AI demand, and the demand right now for these kinds of workloads is high. 

Two sessions made the same point from opposite ends of the price spectrum. Comarch walked through a real migration from x86 to AWS Graviton-based instances, with meaningful cost reductions and measured performance gains. The honest part of their talk: Graviton is not a flag flip. If you have native code, JNI bindings, or JIT-tuned hotspots, you pay for the migration before you see the savings. 

On the other end of the spectrum: Meta’s agreement to deploy AWS Graviton processors at scale, starting with tens of millions of Graviton cores, announced ten days before the summit and explicitly framed around CPU-intensive agentic AI workloads — real-time reasoning, code generation, and multi-step task orchestration. 

For Robots & Pencils, this opens a third option alongside Bedrock and direct provider APIs. For clients with data-residency constraints, predictable high-volume workloads, or smaller open-weight models where managed-API margins make self-managed attractive, the playbook is now well-documented and accessible. Independent benchmarks on Llama 3.1 8B have Graviton4 delivering roughly 2x the tokens per dollar of comparable x86 options for that model class. 

A Practitioner’s Checklist for 2026 

The session that generated the most useful signal for client-facing conversations was DEV209, delivered by Tomasz Dudek, Data and AI Team Lead at Chaos Gears and an AWS Machine Learning Hero. The premise was simple: AI has been mainstream for over three years. He has watched hundreds of Amazon Bedrock projects pass through his hands. Most near-failures trace back to a small set of repeatable mistakes. 

The talk was the inverse of a vendor pitch. Here is exactly how teams stall before the first line of code. Here is what to do instead. He closed with 13 numbered tips for approaching AI projects in 2026. The final line: “Have evals, really.” 

It was good to hear a practitioner at that level land on the same conclusions we have been operating on. The teams doing this work at scale are converging on the same principles, and the list mapped closely to how we already approach agent quality on client engagements. Confirmation from that angle is worth having. 

The Parts That Were Just Fun 

Not everything at a summit is a session worth writing home about. But a few moments, in addition to the Serverlesspresso bar, which was cool enough to warrant a second mention, stood out for the right reasons. 

The AWS Drive Your Data Formula 1 simulator was exactly what it looked like: two Fanatec rigs, full wraparound LED screens, a Canada time-trial, and a results board you could compete on. The pitch underneath was real telemetry and lap analytics. The booth’s job was to draw a crowd, and it absolutely did. The team took turns. 

And the Ukrainian-speaking community was well-represented at this summit. Several familiar-sounding conversations happened in unexpected corners of the expo. That part mattered. 

What the Day Confirmed 

The most useful thing a conference can do is sharpen your picture of where the tools are today versus where they are heading. Warsaw 2026 did that well. 

Agentic AI is no longer a roadmap commitment from AWS. It is the organizing logic of everything they showed. Agent evaluation infrastructure is production-ready and instrumented the way mature engineering teams expect. The compute story has matured to a point where self-hosting is a genuine option for the right workloads, not just a theoretical one. Knowledge graphs as a foundation for enterprise AI agents are getting independent validation at scale. And the practitioners who have been doing this work longest are converging on the same principles around evaluation, quality gates, and shipping agents that are honest about what they know. 

None of that surprised us. All of it was good to see confirmed. 

Warsaw 2026 delivered real technical depth on agentic AI, agent evaluation, and knowledge graphs. The team went in with specific questions and came back with sharper answers, a few useful new contacts, and a strong argument for cloud-ordered coffee at the next internal engineering day. 

Robots & Pencils is an AWS Advanced Tier Services Partner and AWS Pattern Partner. Request an AI Briefing today. 

Written by Bohdan Popovych: Robots & Pencils Ukraine Engineering Manager, Rostyslav Volskyi: AWS Certified Solutions Architect and Amazon Web Services Developer, and Stanislav Makar: AWS Certified Solutions Architect – Professional.  

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We Took a Real Problem into the Amazon Quick Hackathon. It Delivered.

Adrian Bird

I spent last Tuesday at Amazon’s ORD11 office with five colleagues from Robots & Pencils, building on Amazon Quick for the day.  

The Problem We Brought In 

We brought a live use case from one of our enterprise customers, a regulated utility dealing with alarm overload, aging infrastructure they must migrate off by 2028, and the steady departure of the asset experts who know how all of it really works. 

Robots & Pencils at AWS Amazon Quick Hackathon
Photo by Scott Young: Pictured L-R Lisa Bayne, Stefan Deusch, Alex Shumski, Saul Delage, Adrian Bird

What We Built (And What Surprised Me!) 

By the end of the day we had a working end-to-end agentic workflow that includes a dashboard pulling device telemetry into one view, an agent that triages incoming alerts and recommends what to do about them, and a knowledge base that captures the kind of expertise that usually walks out the door when someone retires. It’s nowhere near production, but it’s enough that we are ready to sit down with the customer next week and have a concrete concept discussion instead of a whiteboard one. That’s the part that surprised me most. 

We were also lucky enough to be recognized as one of the winning partners on the day, which was a nice bonus. 

Robots & Pencils at AWS Amazon Quick Hackathon
Photo by Scott Young: Pictured L-R Lisa Bayne, Stefan Deusch, Adrian Bird, Alex Shumski, Saul Delage

A Few Thanks 

A few thanks are in order. Naresh Rajaram, Sr. Partner Solutions Architect at AWS, ran a genuinely well-organized event. Every detail was thought through. Neal Cauley’s framing of where Amazon Quick is heading was probably the most useful 30 minutes of the day for me, and it connected back to what Rima Olinger, World Wide Director Data & AI GTM – Amazon Quick, has been sharing publicly about how Amazon itself is using the product internally. Worth reading if you haven’t. Thanks also to the AWS team for inviting us and to the Quick specialists who sat at our table and helped us push further than we would have on our own. 

Looking forward to the next one. 

Robots & Pencils is an AWS Advanced Tier Services Partner and AWS Pattern Partner. Request an AI Briefing today.  


About the Author 

Adrian Bird is Vice President of AWS Partnership at Robots & Pencils, where he leads the company’s AWS Partner strategy and execution, expanding joint customer engagement, and strengthening alignment with AWS teams. Connect with Adrian.

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Robots & Pencils Expands Retail and Consumer Goods Leadership with Appointment of Saul Delage as Client Partner 

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Robots & Pencils

As AI reshapes how Retail and Consumer Goods businesses compete, Robots & Pencils plants its flag in the vertical and brings in a 30-year industry veteran to lead the charge.

Robots & Pencils, an applied AI engineering partner known for high-velocity delivery and measurable business outcomes, today announced the appointment of Saul Delage as SVP, Client Partner, Retail and Consumer Goods (RCG). Based in Chicago, he brings 30 years of experience building executive partnerships and driving growth across some of the most recognized names in digital transformation. Delage joins a proven leadership team at Robots & Pencils with extensive experience delivering for more than 100 of the world’s most recognized consumer brands, including dozens of Fortune 500 companies.

The appointment is a deliberate move. Robots & Pencils is investing with intention in Retail and Consumer Goods, including CPG, eCommerce, Restaurants & Everyday Essentials, and Retail, an industry under mounting pressure to move from AI experimentation into generative and agentic AI that performs in production and delivers measurable business outcomes. Delage will lead client relationships across the vertical, helping enterprise leaders get more from their AI investments and more from their investments in AWS, while strengthening the company’s presence in key markets and building closer, more embedded partnerships with clients.

The Right Leader for the Moment

“Saul is the kind of leader clients trust before the contract is signed and can’t imagine working without after,” said Len Pagon, CEO of Robots & Pencils. “He has worked alongside some of our team before. He knows how we operate, and he knows this vertical inside out. Retail and Consumer Goods is a large growing industry vertical for us, and we went out and got the right leader.”

A Career Built on Trust and Delivery

Delage arrives with a career forged across Cognizant, Isobar, Havas, Razorfish, and Fry, where he built high-performing growth teams, secured long-term relationships with Fortune 500 companies, and earned a reputation as one of the most technically fluent executives in the industry, equally effective in the boardroom and in the details of delivery.

His hire reflects the company tenet that winning in Retail and Consumer Goods requires leadership with deep business experience, the technical fluency to speak the language of AI, and the delivery discipline to back it up.

“Retail and Consumer Goods businesses have made significant investments in AI, and too many have little to show for it in production,” said Delage. “Robots & Pencils builds enterprise AI systems — generative, agentic, and production-ready — that move fast and tie directly to revenue and customer experience. That is exactly what this industry needs right now, and Robots & Pencils is built to deliver it.”

Built on AWS. Driven by Outcomes.

Robots & Pencils is unabashedly aligned with AWS and is building its Retail and Consumer Goods vertical around that conviction. The goal is helping enterprise leaders drive measurable business outcomes on AWS, from first deployment to full-scale production. For AWS co-sell teams and enterprise leaders who need a partner that moves fast and delivers, that commitment is the differentiator.

Ready to move from AI experimentation to AI execution? Request an AI Briefing.

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Robots & Pencils Goes All in on AWS with Appointment of Adrian Bird as Vice President of AWS Partnership 

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Robots & Pencils

Bird brings two decades of alliance leadership, including five years inside AWS, to accelerate co-sell engagement and expand enterprise AI delivery with AWS 

 Robots & Pencils, an applied AI engineering partner known for high-velocity delivery and measurable business outcomes, today announced the appointment of Adrian Bird as Vice President of AWS Partnership.  

The timing is deliberate. Bird joins as the company deepens its investment in the AWS ecosystem. He will lead the company’s AWS Partner strategy and execution, expanding joint customer engagement, and strengthening alignment with AWS teams. 

Two Decades of AWS and IBM Partnership Leadership 

Bird brings direct experience from AWS, where he was Partner Sales Leader from 2020 to 2026. In that role, he managed comprehensive channel strategy and partner program initiatives across ISVs, global systems integrators, and technology partners, collaborating with AWS field sellers across regions and industries to support joint go-to-market initiatives. He built partner success frameworks that drove exceptional year-over-year growth in partner revenue, created revenue operations tools adopted across multiple AWS business units, and led initiatives that significantly expanded the security partner ecosystem. He earned AWS’s Innovation All-Star recognition in 2024.  

Prior to AWS, Bird spent fifteen years at IBM in progressively senior partnership and alliance roles. He grew the Watson Media worldwide partner channel from inception to more than a third of business unit revenue within two years, scaled the IBM Commerce partner business several-fold over four years, and led the integration of Sterling Commerce’s partner ecosystem following its acquisition, retaining the vast majority of partners while substantially growing combined revenue. He is a recipient of IBM’s Industry Solutions Successful Partnering Award and the IBM 100% Club. 

Accelerating AWS Partnership Strategy 

“Adrian has spent his career building partner ecosystems that generate real, compounding results,” said Scott Young, EVP of Growth and Strategic Partnerships. “Having led partner strategy inside AWS, he knows exactly how AWS field teams operate and what it takes to be a partner they actively bring into deals. That perspective, combined with his track record of execution, is precisely what we need right now. Clients who need enterprise AI at speed will benefit directly from what Adrian builds.” 

“We are unabashedly all in on AWS,” said Len Pagon, CEO of Robots & Pencils. “We have tremendous traction and momentum. Adrian is another key investment in taking our AWS partnership further, faster.” 

Driving Enterprise AI Adoption and AWS Consumption at Scale 

Bird’s appointment builds on recent company milestones including earning AWS Advanced Tier Services Partner status, selection as one of 11 inaugural AWS Pattern Partners globally, and the launch of its Studio for Generative and Agentic AI in Bellevue near AWS headquarters. The company is also actively engaged with AWS through its collaboration with the AWS Generative AI Innovation Center to support joint enterprise initiatives. Bird’s mandate is clear: align partnership strategy with Robots & Pencils’ ability to deploy AI into production at speed and drive measurable AWS consumption and customer value at scale. 

“Robots & Pencils has built what most companies only claim to have. They have the engineering depth, a proven record of deploying AI into production at speed, and the scale to serve enterprise clients globally,” said Bird. “The AWS partnership is the force multiplier that connects those capabilities to the clients who need them most. My job is to make sure that potential becomes performance, for Robots & Pencils, for AWS, and for the clients we serve together.” 

Request an AI briefing to evaluate how applied AI can deliver velocity and impact within your organization.

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Robots & Pencils Appoints Jason Lacy as Client Partner to Lead Education Vertical

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Robots & Pencils

Veteran executive brings three decades of experience guiding institutions, edtech platforms, publishers, and workforce organizations through digital transformation and applied AI modernization.

Robots & Pencils, an applied AI engineering partner known for high-velocity delivery and measurable business outcomes, today announced the appointment of Jason Lacy as Client Partner, Education. Lacy will lead the company’s education vertical, expanding its work across the full education ecosystem.

Explore how Robots & Pencils accelerates AI and cloud modernization in higher education.

Strengthening Leadership Across the Education Ecosystem

Education has been a core focus for Robots & Pencils since its earliest days. Lacy’s appointment strengthens that commitment with dedicated leadership grounded in deep sector knowledge, platform expertise, and enterprise execution.

“Jason has a deep passion for education and brings decades of experience delivering outstanding results and outcomes for education clients,” said Len Pagon, CEO of Robots & Pencils. “He brings a rare blend of market leadership, real education expertise, and technical depth. He understands how institutions help students and enable faculty, how platforms scale, and how to turn AI strategy into production systems that perform. Education leaders need partners who combine ambition with discipline. Jason brings that balance, and it elevates what we can deliver across the sector.”

Lacy’s 30 years of experience spans global partnerships, enterprise technology strategy, and revenue-aligned growth. Most recently, as Senior Vice President of Global Partnerships at Learnosity, he led a worldwide ecosystem representing a significant share of organizational revenue across assessment, learning technology, and workforce certification platforms. He built and scaled partner programs, advanced complex integrations, and aligned commercial strategy with product innovation to drive sustained growth.

Earlier in his career, Lacy expanded strategic partnership practices at Unicon and strengthened relationships across major publishers, platforms, and institutional stakeholders. With a foundation in software engineering and system architecture, he evaluates integration pathways with precision and translates complex technical capabilities into enterprise value. He has advised institutions across public, private, and online sectors, edtech platforms and publishing organizations on digital transformation, ecosystem strategy, and outcome-based modernization initiatives.

Focused Leadership for AI and Cloud Modernization in Education

In his role, Lacy will guide education clients as they modernize legacy infrastructure, strengthen data foundations, and operationalize artificial intelligence within accountable, enterprise-grade environments.

“Education institutions carry both public trust and generational responsibility,” said Lacy. “Innovation must move forward, but it must do so responsibly. The right technology strengthens operational performance while keeping student success at the center.”

AI Patterns Accelerate Responsible AI Adoption in Education

Robots & Pencils’ AI Pattern framework makes this possible with velocity and impact. This structured, repeatable solution model combines proven architecture with use-case-specific configurations to compress delivery timelines from months to weeks.

“When I looked at Robots & Pencils’ AI Pattern approach, I immediately saw its relevance for education,” said Lacy. “Education leaders operate within rigorous governance and risk frameworks. They need progress they can trust. AI Patterns provide a disciplined, repeatable foundation that allows institutions to move quickly on targeted priorities while maintaining control.” 

Robots & Pencils views this early traction as the catalyst for sustained partnership, enabling institutions to expand AI capabilities through phased modernization strategies that advance enrollment growth, student retention, student success analytics, academic operations, enterprise data strategy, and secure adoption.

As an AWS Advanced Tier Services Partner and AWS Pattern Partner, Robots & Pencils plays a guiding role in defining how enterprise AI systems are productized and scaled. That experience strengthens the company’s ability to bring structured, production-ready AI systems to complex institutional environments.

A Longstanding Commitment to Education Innovation

“Everything we build begins with the belief that the best AI systems emerge when engineering discipline meets human-centered design,” said Pagon. “Education sits at the intersection of mission and modernization. With Jason leading our education vertical, we are strengthening our ability to help institutions scale AI responsibly while staying true to the people they serve.”

Robots & Pencils has partnered with education institutions and platforms for well over a decade, modernizing legacy systems, launching cloud-native products, and building digital experiences used by millions of learners. Lacy’s appointment reinforces the company’s long-term investment in education and its commitment to helping leaders translate AI ambition into secure, scalable systems that perform in production.

Education continues to evolve. Robots & Pencils is building the AI and cloud foundations that enable that progress, with Jason Lacy helping guide the way.

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Robots & Pencils Achieves Amazon Web Services (AWS) Advanced Tier Partner Status

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Robots & Pencils

Milestone reinforces Robots & Pencils’ strength in building and operating cloud-native and AI-enabled systems on AWS 

Robots & Pencils, an applied AI engineering partner known for high-velocity delivery and measurable business outcomes, today announced it has achieved AWS Advanced Tier Partner status. The designation marks a significant milestone in the company’s continued growth, delivering production-grade systems on AWS for enterprise organizations.

Explore how Robots & Pencils delivers applied AI and cloud-native systems built to operate at enterprise scale. 

AWS Advanced Tier Recognition Reflects Production-grade Delivery at Enterprise Scale

AWS Advanced Tier Partner status recognizes organizations with demonstrated depth in AWS delivery, technical expertise, and customer success at scale. Partners at this level consistently design, build, and operate secure, resilient, and scalable systems running in production. Robots & Pencils earned this designation through sustained enterprise delivery, a strong bench of AWS-certified engineers, and real-world workloads running on AWS.

A High-Velocity Alternative to Traditional Global Systems Integrators

Robots & Pencils operates as a nimble alternative to traditional global systems integrators, pairing AWS-native architecture with a relentless focus on velocity and impact. Small, senior, highly focused teams move quickly from idea to execution, delivering production-ready systems that create value early and improve continuously through real-world learning.

“Our AWS Advanced Tier designation continues to build on strong momentum as we strengthen our relationship with AWS,” said Len Pagon Jr., Chief Executive Officer of Robots & Pencils. “In December, we were selected as one of 11 AWS Partners out of more than 190,000 to join the new Pattern Partner program. In January, we launched our Bellevue, WA Innovation Center next door to AWS HQ to work closely with the AWS GenAIIC team. Now, as an AWS Advanced Tier Services Partner, we have access to additional AWS funding for proofs of concept and substantial resources to support our clients.”

Building and Operating Generative and Agentic AI Systems that Scale

Enterprise leaders continue accelerating modernization and AI initiatives that demand speed, reliability, and operational maturity. 

AWS Advanced Tier status signals that Robots & Pencils brings disciplined execution and rapid iteration to move confidently from strategy to production and scale. Clients gain earlier insight, reduced delivery risk, and steady progress aligned to clear business outcomes.

“Enterprises are moving quickly toward generative and agentic AI systems that operate as an enablement layer of their business,” said Jeff Kirk, Executive Vice President of Applied AI at Robots & Pencils. “AWS provides a powerful foundation, and our role is to design and deliver AI systems that integrate securely, perform reliably, and scale with confidence. Advanced Tier recognition affirms our ability to move AI from ambition into production.”

Certified Talent and Engineering Discipline Behind AWS Advanced Tier Recognition

The AWS Advanced Tier recognition also reflects the company’s investment in certified talent, security discipline, and operational excellence.

“AWS Advanced Tier status is earned through consistency, accountability, and a deep commitment to craft,” said Nicholas Waynik, Vice President of Engineering at Robots & Pencils. “Our engineers invested the time to master the platform, earn the certifications, and apply that knowledge to systems running in production. This recognition reflects the standards they hold themselves to every day and the trust our clients place in their work.”

Enterprise-ready AI Architectures Delivering Impact Across Industries

Robots & Pencils also holds AWS Pattern Partner recognition, highlighting its strength in delivering repeatable, enterprise-ready architectures for applied AI and intelligent systems. This capability complements Advanced Tier status by reinforcing architectural leadership alongside delivery maturity, while maintaining a clear focus on execution that performs in production.

Robots & Pencils delivers application modernization, cloud-native product development, data platforms, and AI-enabled systems on AWS across Consumer Products and Retail, Education, Energy, Financial Services, Healthcare, and Manufacturing. These solutions support regulated environments, high-growth digital products, and complex enterprise ecosystems where reliability and scalability matter every day.

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Accelerating Innovation with AWS: Robots & Pencils Selected as an AWS Pattern Partner 

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Robots & Pencils

Today, Robots & Pencils joins AWS as a launch partner in the AWS Pattern Partners program, an invite-only initiative that works with a select cohort of consulting partners to define how enterprises adopt next generation AI and emerging technologies on AWS. 

As a Pattern Partner, Robots & Pencils brings proven success with emerging technologies on AWS, including AI/ML, Generative/Agentic AI, Robotics, Space Technology, and Quantum. The program focuses on accelerating enterprise adoption through repeatable, scalable patterns that encode tested ways to solve specific business problems, with architecture, controls, and delivery practices that have already been validated with customers. 

For customers, selection of Robots & Pencils into this program signals that AWS has reviewed and endorsed both the outcomes and the operating model behind the work delivered in these domains. Enterprises that face pressure to modernize critical processes, adopt AI safely, and respond to new regulatory and security requirements gain access to patterns that have already delivered measurable results. 

Pattern Partners also sets a clear horizon view for emerging technology. In the near term, it concentrates on AI/ML, Generative & Agentic AI patterns, including sub domains such as Process to Agent (P2A), Agent to Agent (A2A), Responsible AI, and RegAI. Over the midterm, the program extends these capabilities into connected environments that use Robotics, IoT, and Edge and Space Technology on AWS. For the long term, it explores Quantum and next generation enterprise innovations, aligning new capabilities with existing AWS investments in data, AI, and security as they mature into reliable patterns. 

Our Pattern: Enterprise Document Intelligence Platform 

At the heart of the participation of Robots & Pencils in Pattern Partners is a flagship pattern that the company is co-developing and scaling with AWS. 

The Customer Problem 

Organizations in Energy, Manufacturing, and Health & Wellness face a common set of challenges. Data and workflows sit in disconnected systems, which slows AI adoption and creates duplicated effort. Teams find it difficult to govern AI models and agents at enterprise scale, especially when regulations and internal standards move quickly. Talent and process gaps make it hard to adopt new technology in a way that satisfies risk, compliance, and operational leaders. 

Our Joint Approach with AWS 

Together with AWS, Robots & Pencils has designed the Enterprise Document Intelligence Platform. This pattern combines an architecture built natively on AWS using Amazon Bedrock, Amazon SageMaker, and Amazon Bedrock AgentCore, an operating model with clear roles, runbooks and guardrails for IT, data, security and business teams, and accelerators such as pre-built integrations, automations, policies, templates, dashboards and agents. This pattern is being refined through a time boxed incubation with a set of lighthouse customers. As it matures, it is packaged as a Pattern Package so that more joint customers can adopt it rapidly with consistent results. 

Early Results 

Early adopters are already reporting tangible outcomes from the Robots & Pencils’ Enterprise Document Intelligence Platform. With 2 million interactions across 100,000+ users, customers reported a 90% satisfaction score and 40% improved confidence in responses from the pattern. 

As these results are validated across additional lighthouse customers, the Pattern Package becomes available to AWS field teams globally. This enables customers in new regions and sectors to benefit from the same proven approach without restarting design from the beginning. 

How the Pattern Partners Program Works with Customers 

When a customer engages Robots & Pencils through the Pattern Partners program, the engagement starts from a proven blueprint, not from scratch. The Pattern Package already encodes successful implementations, including architectures, guardrails, and playbooks. Customers receive coordinated support from AWS specialists, the AWS Consulting COE Pattern Partner team and experts from Robots & Pencils across consulting, engineering, and product. 

The program design supports fast yet responsible experimentation. Customers can move from idea to live pilot while maintaining enterprise grade security, compliance and governance. The pattern also includes a clear path from pilot to scale, so organizations can extend from initial deployments to cross region and multi business unit rollouts with ongoing optimization. 

Being part of the AWS Pattern Partners program allows Robots & Pencils to bring emerging AWS capabilities such as Generative AI and Agentic applications to customers earlier. Guardrails and controls stay clear and well defined. The company can turn its strongest customer successes into repeatable assets that benefit a wider set of organizations. Collaboration with AWS field teams, solution architects and service teams keeps the pattern aligned with the latest platform innovation. Robots & Pencils also contributes back to the broader AWS partner ecosystem by sharing learnings and raising the standard for how emerging technology is adopted. For customers, this approach reduces risk, increases predictability, and accelerates business impact from AWS investments. 

Partner Perspective 

“Joining AWS Pattern Partners is a strategic milestone for Robots & Pencils,” said Jeff Kirk, Executive Vice President of Applied AI, Robots & Pencils. “With our Enterprise Document Intelligence Platform, we turn our strongest customer wins into a clear, repeatable path to reduce onboarding time for customers in need of intelligent search, and increased confidence in the accuracy of the results, so customers can move from pilots to production with greater speed, control and confidence.”  

AWS Perspective 

“AWS created Pattern Partners to work with a select cohort of builders who can set the standard for how enterprises adopt emerging technology on AWS. Robots & Pencils brings deep expertise in KnowledgeOps, including RAG and compound systems, and a proven pattern in the Enterprise Document Intelligence Platform that is already delivering measurable outcomes for customers,” said Brian Bohan, Managing Director of Consulting COE, AWS. “We look forward to scaling this work together and bringing these benefits to more joint customers across industries.”  

Next Steps 

Customers interested in these patterns can speak with Robots & Pencils through Robotsandpencils.com/contact to review current challenges and identify which patterns are most relevant. 

Those that want to explore Enterprise Document Intelligence Platform in depth or learn how the AWS Pattern Partners program could support their own roadmap can request a focused discovery session. In that conversation, AWS and Robots & Pencils work with stakeholders to map business challenges to the pattern, estimate potential impact, and define a practical path to adoption. 

Together, AWS and Robots & Pencils look forward to turning critical business challenges into repeatable, scalable patterns for growth. 

The pace of AI change can feel relentless with tools, processes, and practices evolving almost weekly. We help organizations navigate this landscape with clarity, balancing experimentation with governance, and turning AI’s potential into practical, measurable outcomes. If you’re looking to explore how AI can work inside your organization—not just in theory, but in practice—we’d love to be a partner in that journey. Request an AI briefing. 

Key Takeaways

  • Robots & Pencils has been selected as a launch partner in the invite-only AWS Pattern Partners program, recognizing leadership in next generation AI and emerging technologies.
  • The joint Enterprise Document Intelligence Platform provides a validated, repeatable pattern that helps enterprises adopt Generative and Agentic AI with confidence.
  • The pattern incorporates AWS native services such as Amazon Bedrock, Amazon SageMaker, and Amazon Bedrock AgentCore, along with an operating model, runbooks, guardrails, and pre-built accelerators.
  • Early lighthouse customers report strong outcomes including high satisfaction, increased confidence in accuracy, and millions of successful interactions.
  • The program gives organizations a faster, clearer path from idea to pilot to full scale rollout, supported by coordinated teams across AWS and Robots & Pencils.
  • Enterprises gain access to patterns that reduce risk, increase predictability, and produce measurable business impact from AWS investments.

FAQs

What is the AWS Pattern Partners program?

It is an invite-only AWS initiative that works with a select group of consulting partners to define how enterprises adopt next generation AI and emerging technologies through validated, repeatable patterns.

Why was Robots & Pencils selected as a Pattern Partner?

AWS recognized the company’s proven outcomes across AI and emerging technologies, as well as its track record delivering measurable results with scalable architectures and operating models.

What is the Enterprise Document Intelligence Platform?

It is a jointly designed pattern that uses AWS native services and accelerators to help organizations unify data, streamline governance, and deploy Generative and Agentic AI across complex environments.

Which AWS technologies power the pattern?

Key services include Amazon Bedrock, Amazon SageMaker, and Amazon Bedrock AgentCore, along with AWS controls, security practices, and operational frameworks.

Who benefits most from this pattern?

Enterprises in sectors like Energy, Manufacturing, and Health and Wellness that face challenges with disconnected data, evolving regulations, and the need for responsible AI adoption at scale.

What results have early adopters seen?

Customers reported 2 million interactions across more than 100,000 users, a 90 percent satisfaction score, and a 40 percent improvement in confidence in response accuracy.

How does the program support faster innovation?

Organizations begin with a proven blueprint rather than a blank page. This accelerates pilots while maintaining enterprise grade governance and provides a clear pathway to large scale deployment.

How do customers engage?

Teams can connect through Robotsandpencils.com/contact to discuss current challenges or request a focused discovery session to understand fit, impact potential, and next steps.

What does this mean for long term innovation?

The program continually extends into new domains, guiding enterprises through emerging capabilities such as Robotics, IoT, Space Technology, and Quantum as they mature into reliable patterns.

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