About me
Brian Bawuah
Product engineer with a human-centred focus. I build AI products at the intersection of engineering, design, and the user.
How I work
I started LAB-BAWUAH because the best digital products emerge where engineering, design, and the user meet, and that intersection rarely survives three vendor handoffs. End-to-end product engineering keeps the human side alive at every layer instead of leaving it for whoever ships last.
Background
Years of frontend and platform work in enterprise environments. Most recently embedded inside a high-assurance customer building a multi-modal AI platform: video and audio intelligence, document RAG, semantic search, and language services. That experience shapes how LAB-BAWUAH now works with other teams building serious AI products.
Tools and stack
Elasticsearch (hybrid BM25 + vector, RRF, semantic templates), llama.cpp / llama.rn with Gemma and other quantized open-weight models, ArgoCD on Kubernetes, React / React Native, and security-hardened SSR with strict CSP. TypeScript everywhere there's a UI.
Outside work
Chelsea FC and Ajax. LEGO. Writing about systems with less hype and more clarity. See the articles for that side.
What I build
Search and AI orchestration. Vision and document intelligence. Secure deployment. The interface on top.
Search, retrieval & AI orchestration
Designing systems that turn questions into answers. Hybrid retrieval that mixes keywords with meaning, agentic pipelines that orchestrate models and tools, and structured outputs the rest of your stack can rely on.
Computer vision & document intelligence
Pulling structure out of images, scans, and documents that were never designed to be machine-readable. OCR, layout analysis, and visual models that turn pages into something you can search and reason over.
Sovereign & secure systems
AI that runs where the data lives. On a phone, in an air-gapped network, behind a security perimeter. A modern AI stack with none of the round-trips to someone else's cloud, built to survive a serious security review.
Product engineering & interface design
Real products shipped to real users. Interfaces designed around the person on the other end, not the data model underneath. Engineering that holds up at scale and looks good doing it.
How I engage
Engagements are scoped to your reality: how much you've already figured out, what you can hand over, and the constraints of the environment you're building in.
01Embedded engineer
I join your team for a fixed-term engagement and ship inside your environment: code, deployments, security review. Best when you have a product to build and need a senior pair of hands who already speaks the stack.
02Advisory & architecture
Shorter scope: I review your AI architecture, retrieval design, or product strategy and write a concrete recommendation you can build from. A useful checkpoint before locking in a direction.
03Fixed-scope build
A bounded deliverable: a RAG prototype on your own corpus, an on-device LLM proof-of-concept, a frontend for an existing model. Quoted up front, shipped end-to-end.
Engagements
LAB-BAWUAH is product engineering for AI: the model work, the deployment, and the interface as one job rather than three. If you've got an AI product to build, wherever it lives, get in touch.