A small team of senior engineers partnering with you to ship. We cover your AI engineering needs :: long-term or ad-hoc :: designing and building your AI project, or augmenting the team you already have.
End-to-end delivery:: we scope, build, and roll the feature out to production.
Managed beyond launch:: ongoing support, fixes, adjustments, and the next thing you want built.
Full stack:: AI architecture, AI features, cloud, code, and infrastructure under one team.
Recently shipped for
What we ship
Things we ship the most.
Agents :: autonomous systems that reason and act.
Agents that plan, decide, and execute against your real systems :: not scripted flows with a chat skin. They reason over your data, choose which tools to call, run multi-step work, recover from failure, and stop when the job is done. The interface is whatever fits :: a UI, an API, a scheduled job, a voice channel :: the intelligence sits underneath.
Built end-to-end: the agent loop itself, the tool and retrieval layer, the memory model, the guardrails, and the eval harness that keeps behaviour steady as you ship. We test across model families :: Anthropic, OpenAI, self-hosted :: and pick what fits the latency, cost, and accuracy your case actually needs.
Company knowledge :: actively kept, agent-accessible.
A company knowledge base an agent can actually use :: not a dumping ground of PDFs. Ingestion pipelines that handle mixed formats, structures, and languages, with chunking and metadata tuned to how your team asks questions.
The point is institutional memory :: a real track record of decisions, processes, and documents the company can actually reach for. Onboarding becomes pointing at the agent instead of reassembling tribal knowledge. Process design becomes a conversation with what's already documented. Optimisation comes from asking the corpus what it already knows, rather than guessing.
RAGIngestion pipelinesCitationsDomain experts
AI & cloud engineering :: the wiring that makes it production.
The unglamorous half that decides whether an AI feature is a demo or a product. Cloud architecture, deployment pipelines, CI/CD, observability, cost controls :: everything between the model call and a system real users can rely on.
Classical engineering is still very much part of the craft. APIs, data models, queues, schedulers, auth, tests :: the surrounding software that decides whether anything holds up under load :: is something we still write, still master, and still take seriously. We are not AI-exclusive and not AI-blinded; the model is one component, and we treat the rest with the same rigour as a project that had no model in it at all.
AWSPythonCI/CDObservability
From investor pitch :: to first users :: to live in the stores.
Adam, the founder, came to us in late 2024 after two earlier attempts to get the technology off the ground. He had a co-founder and a clear product vision :: a niche social app, best-in-class social mechanics paired with AI, built for a specific community rather than the generic feed :: but no working backend, no infrastructure, and two developers who had walked away once they understood the real scale: a long-term build covering architecture, cloud, deployment, and CI/CD, not a weekend project.
We took ownership of the engineering side end to end. Backend kicked off in November 2024, the first alpha shipped in March 2025 :: enough for Adam to run his first investor pitch :: beta followed in June, and 1.0 went live on iOS and Android in March 2026, after a second private round closed on the back of the beta. We own the backend, the cloud, the deployment pipelines and CI/CD, the data layer, and the AI features the app is built around: search, moderation, and image recognition for things like plants and plant diseases.
We work the way real startups do :: short cycles, fast feedback, decisions made in the same channel as the code. The app launched free, hit the Top 20 in Social within two weeks, and has run without a single production incident. Adam now leads a growing in-house team alongside us :: mostly on the frontend :: while we keep shipping on the backend, hardening what's in production, and scaling the platform as regular users and business collabs come on board.
One of the software houses we consulted estimated the work would take two years. Emil and a frontend developer delivered the MVP in five months. He remains the best engineer I have ever worked with.
Mobile appAI featuresPaymentsRegistrationInvestor demo
A trial specialist :: on-call :: built for the investor pitch.
In late 2025 we built an agent POC for Agentic Pharma, against a sharp brief: a working demo, ready in time for the investor pitch. The founders :: Sridhar and Maruthi, two doctors with deep biotech and pharma R&D backgrounds :: wanted to prove something specific: that an AI agent can sit on top of oncology trial data and behave like the specialist who actually ran the study. Time-poor physicians and trial teams getting accurate, sourced answers on demand, rather than hunting through PDFs for an hour.
We built the POC end to end in a month. The agent itself, the retrieval layer that grounds every answer in a specific document, and the ingestion pipeline that brings new studies in on demand :: non-trivial, given a corpus of trial files in different formats, languages and structures, with the meaningful signal often buried in dense tables of numbers. On top of that, the numerical tooling that lets the agent reason over the data, compute trial insights, generate on-the-fly charts and dashboards, and the UI to drive the whole thing on stage. We tested across multiple model families :: Anthropic and self-hosted :: picking the right one per task.
The result reads like a trial specialist with the receipts attached: drop in a study, ask anything, and the answer comes back grounded, cited, and quantified. Built as a POC for the fundraising round, it's the foundation for the bigger ambition :: a B2B SaaS for biotechs, multiple specialised agents, and custom models trained against each client's own dataset. We're set up to keep building it with them once the round closes, in the same long-term partnership model we run on every project.
AI agentOncology trialsRAGCharts & dashboardsInvestor demo
From phone calls :: to a 24/7 agent :: handling driver applications end to end.
We built and shipped an AI agent into the jobs portal of a California-based trucking media company, against a clear pain point. Their jobs portal carried thousands of offers, each one detail-heavy, and drivers couldn't get through them on their own. Most ended up calling or emailing the team to narrow things down :: which then meant recruiters calling drivers back for the missing details before an application could even start. The company isn't a tech shop, didn't have an AI engineer in-house, and wanted a partner who could just take the problem and ship it.
We started with a 3-week POC :: a chat agent dropped into the portal that drivers could actually talk to. It worked well enough that the brief expanded into a full MVP, shipped in another six weeks. The agent is context-aware: it knows when a driver is sitting on a specific offer and goes deep on it, and falls back to a more general mode on the main screen. It carries the conversation across sessions, remembering what the driver has applied to and what they were looking at last time. It gathers what an application actually needs :: location, salary, experience, home address, particulars like a pet on board :: then registers the application in the company's system and notifies the partner doing the hiring.
It's been live since September 2025 and the impact reads like an always-on customer service line: the calls and emails that used to bottleneck the team are now handled in chat, around the clock, by an agent that knows the catalogue and the driver. The client trusted us to own the build end to end :: they're not a tech-first company, and that's exactly the kind of project we're built for.
AI agentChat integrationJob matchingDriver applicationsPOC → MVP
Started shipping production code in 2016. Spent the first half of his career inside corporates :: building for FinTech, Media & Entertainment, live sports, and gaming :: before moving full-time to startups, where the work is faster and the stakes are real.
Specializes in AI engineering: agents, RAG, automation pipelines, and the infrastructure that makes them production-grade. Still writes code on every project, not just runs them.
10+ years in. That experience :: shipping at scale inside corporates, then building from zero alongside founders :: is what Emil brings to every project at pocmvp.ai.
The Bench
Backed by a small bench of senior engineers :: 30+ years combined :: pulled in per project. Generalists who can take a product end-to-end, with deeper focus on the technical core.
FAQ
Questions clients actually ask.
01What's the difference between a POC and an MVP for you?
A POC proves the risky part works, usually the AI, the agent, or the integration that nobody's sure is feasible yet. Weeks of work, narrow scope, built to run live so the part central to your case actually convinces - whether that's an investor, a board, a client, or your own team. An MVP is the first version real users touch, a product not a demo, built to ship and grow into. A month or more, real architecture, real tests. AI features are where we have the most reps, so if that's what your project hinges on, that's the part we'll make sharpest. If you're not sure which you need, that's the first thing we figure out on the call.
02We're an established company, not a startup - is this a fit?
Yes. The POC, MVP, and AI-feature work we do isn't tied to company stage - it's tied to the project. We've shipped for funded startups and for established companies that simply needed an AI capability built and didn't have the in-house team for it. If you have an AI project to take on, an integration to prove out, or a feature to add to a product already in production, that's squarely what we do.
03How fast can you start?
Usually within a week of the first call. We take one new project a month, so timing depends on what's already in flight - book a call and we'll tell you the next open slot honestly.
04What does a typical engagement cost?
Scoped per project. POCs and short MVPs are typically fixed-scope, fixed-price; longer or augmentation work is monthly. Send a brief and you'll get a real number back, not a range that means nothing.
05Can you work alongside our existing team, or only as the team?
Both. We can drop in as your full engineering team, or augment the team you already have - pairing with your engineers on the AI parts, the infrastructure, or whatever's blocking the roadmap.
06Can you help with AI features on a product we already shipped?
Yes, that's a third of what we do. We come into existing codebases to add agents, RAG, automation pipelines, or whatever the AI feature actually needs to be. We don't insist on rewriting what's already working.
07What happens after launch, do you stick around?
Yes, by default. Most projects roll into an ongoing engagement: new features, AI capabilities, scaling work. You can also wrap things at launch and call us back ad-hoc - we don't lock you in.
08What tech do you work with?
Core is Python for AI and backend services, plus DevOps and cloud infrastructure on AWS. On top of that we ship visuals with Node, Next.js, TypeScript, React, and React Native when the product needs a UI. We pick the stack that fits the product and the team that'll inherit it, not the one we want to learn this quarter.
09Do you sign NDAs and assign IP?
The code is yours from day one. NDA before any specifics get discussed, full IP assignment in the contract - everything we write transfers to you, no licenses, no carve-outs.
10What if I don't have a spec, just an idea?
That's most of our projects. The first call is where we turn the idea into something scopable - what to build first, what to cut, what to validate before writing code.
11Can we meet in person?
Yes, once the project's running and a relationship is built. We start remote and async, and meet in person when it's useful or you ask for it, whichever side of the trip makes sense.
12Where are you based, and what's the legal entity?
Based in Poland, working with clients across Europe and the US - async-friendly, in-person when it helps. Registered as Emil Rafalko, Jurowiecka 76, 16-010 Wasilków, Poland - EU VAT PL9662167318.
13Can I join the team?
If you're a senior engineer with shipped products behind you and you'd want to work on POCs, MVPs, and AI features for startups - drop a note to hello@pocmvp.ai with what you've built. We grow the bench slowly and on purpose.
Ready when you are
Have an idea? Let's scope it in 30 minutes.
Honest answer on whether we can build it, what it'll take, and when you'll see it.
