AI & Automation
Transformative intelligence and autonomous workflow systems — designed to be safe, observable, and genuinely useful in production, not just a demo.
Capabilities that ship to production
How an AI & Automation engagement runs
We de-risk before we build — a short evaluation phase proves the approach before anything ships to users.
Evaluate
Prove the model on real data with a clear success bar before committing to build.
Design & guardrail
Define scope, fallbacks, and observability so the system is safe and reversible.
Build & integrate
Ship into your stack with tests, evals, and monitoring from day one.
Operate & improve
Track quality in production and retrain as data and usage evolve.
A support agent that closes 80% of tier-1 tickets
A RAG-powered agent grounded in the client's knowledge base, with guardrails, evals, and clean human handoff when confidence drops.
Read the case study ↗The tools we build with
Model-agnostic on purpose: the orchestration layer is built so a model swap is a config change, not a rewrite.
Models
Orchestration
Retrieval & data
Evals & ops
AI & Automation FAQ
Related work
Related reading
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