Industry
Production agentic systems — past the prototype, into the audit and the cost review.
We work with software teams that have already shipped an LLM feature and now need it to clear SOC 2, a platform-cost review, an incident-response runbook, and a model-provider outage. The interesting engineering happens after the demo — observability, eval, cost governance, the human-in-the-loop layer. That's where we come in.
Who we serve.
SaaS platforms
Embedded agentic features inside your product — customer copilots, internal-knowledge agents, workflow automation — that clear an SOC 2 conversation and a cost-per-user review before launch.
Fintech and regulated industries
Agentic systems with audit trails the regulator can read, action gates the compliance team controls, and a model-fallback policy that doesn't break a quarter when one provider has an incident.
B2B platforms and marketplaces
Retrieval-augmented agents over your knowledge base and operational data — search, summarisation, internal ops automation — with citation discipline and freshness guarantees the operations team trusts.
Enterprise innovation labs
Pre-product custom ML, eval harness design, and the bridge between a cloud PoC and an edge-deployable artefact your product team can actually ship.
Considerations we engineer for.
- Model-agnostic architecture — Claude, GPT, Gemini, open-weights are configuration choices, not lock-in
- MCP-native tool integration so the agent's surface area is auditable and rate-limited per integration
- Cost-per-task SLOs, not just accuracy SLOs — token spend is engineered, not absorbed
- Human-in-the-loop gates on any consequential action (money movement, customer record changes, external comms)
- Eval harnesses that the buyer's team can run — not opaque internal scoring
- DPDP / SOC 2 / GDPR posture engineered in, not retrofitted at audit time
Stuck between PoC and production?
Tell us what you've shipped, where it broke, and what the audit and cost reviews are telling you. We come back within one working day.