— AI products
Production AI: agents, RAG, automations. With evals, observability, and a fallback for when the model has a bad day.
What this engagement actually looks like — start to ship.
Most "AI software" is a demo held together with duct tape. We build production systems: agents that handle real workflows, retrieval pipelines that actually retrieve, and the boring infra (eval suites, prompt versioning, cost dashboards) that lets you tell what changed and why.
We work with the major model providers — Anthropic, OpenAI, Google, open-weight via Together — and we will pick the right one for your job, not the one with the loudest marketing.
Every potion, fully labeled.
- 01Agent or pipeline architecture doc
- 02Production codebase with structured outputs
- 03Eval suite (golden + adversarial cases)
- 04Cost & latency dashboards
- 05Prompt versioning and rollback flow
- 06Human-in-the-loop fallback paths
Receipts, not promises.
Acme Co. — agentic ops dashboard
An internal copilot that triages support tickets across Linear and Slack with full audit trail. 70% reduction in manual triage.
Layered Ops — eval-driven RAG
A retrieval system over 12 years of incident reports, with a 200-case eval suite gating every prompt change.
Common questions, answered.
01Which model providers do you use?
Anthropic Claude is our default for reasoning-heavy work. OpenAI for fast-and-cheap. Open-weight models on Together or Modal for sensitive data or cost-sensitive workloads. We mix where it makes sense.
02How do you handle cost overruns?
We instrument every call from day one. Per-customer cost dashboards, hard daily caps, automatic graceful-degradation when budgets are approached.