Demonstrated capabilities
A consulting firm shows a capability matrix; we show one that is graded from our own repositories. Every brief carries a maturity ladder with the achieved rungs marked, the evidence behind the grade, and — where we're not there yet — the named gap and the next upgrade.
AI Operations Engineering & Continuous Improvement
Manufacturing-grade operations discipline — CAPA, RCA, and process control — applied to building and running AI systems.
Human-in-the-Loop & AI Governance
Approval gates, fail-closed permission engines, and privacy tiers that keep humans in command of agent actions.
Agent Memory & Knowledge Systems
Persistent, queryable memory architectures — from thread context to a self-hosted bitemporal knowledge store.
Conversational AI Platforms
Production WhatsApp and Telegram systems — multi-client engines, persistent sessions, containerized transports.
Multi-Agent & Deliberation Systems
Councils of models that deliberate on real decisions, and a fleet of agent workstations deployed from one engine.
Retrieval & RAG Systems
Hybrid semantic search with reranking over owned vector infrastructure — and the judgment to know when retrieval is premature.
AI Observability & Evaluation
Trace ledgers, audit rows, and always-on session recording — with formal LLM evaluation as the honest gap in progress.
AI Product Development
Taking AI systems from concept to working software — schema-first, acceptance-criteria-driven, honestly staged.