02 · Agents, automation, governance
AI Orchestration
Most AI pilots stall between proof-of-concept and production. We design and ship multi-agent systems that compose your existing tools, knowledge bases, and APIs into governed workflows the business can actually rely on.
The problem you are probably feeling
Your team is impressed by demos but doesn't trust them in production. The cost line is unclear, the failure modes are unclear, and nobody owns the rollback path.
How the engagement runs
Scoped AI pilot — 4–8 weeks to ship one orchestrated workflow into production, with the patterns and guardrails your team can extend.
What you walk away with
- One production-grade agent workflow scoped to a real business problem
- MCP servers for the 2–3 tools the workflow needs
- Evaluation harness and observability for accuracy + cost
- Governance pattern (human-in-the-loop, audit trail, kill switch)
- Runbook and on-call handoff to your team
Sample artifacts
Specific deliverables vary with the engagement, but typical artifacts include:
- Agent topology diagram with trust boundaries
- Eval set and scoring rubric calibrated to your domain
- Cost-vs-accuracy curves for model selection