AI & agentic systems

Most AI initiatives stall between “interesting” and “in production”: the valuable knowledge lives in people’s heads, compliance fears block the first step, and demos never touch real work. Our answer is a governed pilot, measured in days, not quarters.

What we do

• Governance and compliance analysis. We review your AI governance posture, your existing cloud services (Microsoft 365 or Google Workspace) and the sensitivity of your data, and produce a “safe-to-automate” map.
• Work and tooling proposal. A concrete plan for the tasks you chose, a tooling shortlist that fits your stack and your compliance rules, effort and sequencing, and a definition of success.
• Pilot workshops on real tasks. Recorded sessions in which we execute the dull, repetitive work together with your people and capture the process knowledge that was never written down.
• Working draft model. Agents, supporting apps and microservices scoped to what we observed in the workshops, with full documentation of the process and the design decisions.
• Production build and run. Agents, RAG and integrations with your existing systems, MLOps and AI infrastructure, and the AI roadmap and generative-AI policy to go with them.

How an engagement runs

Five phases, 9–11 person-days of core work, with an off-ramp after every phase: preparation (1 day), governance and compliance analysis (2), work and tooling proposal (2), pilot workshops (2) and the draft model (2–4). It starts with an NDA and two or three candidate tasks that we pick together. Phases, deliverables and next steps are on the AI pilot page.

What you get

A “safe-to-automate” map, a tooling proposal you can act on or shelve, captured process patterns, complete documentation, and a draft model you can see run rather than just read about. Then a decision about production made on evidence from your own work.