AI products

We take an agent from use case to production: a short paid discovery to pin the workflow and data, an architecture with structured outputs, an eval suite (golden + adversarial cases), cost and latency dashboards, and human-in-the-loop fallbacks — then a clean handover or ongoing support. The unglamorous parts (evals, cost caps, fallbacks) are what separate a shipped agent from a demo.

Both, honestly scoped. For a well-defined workflow, a no-code automation (n8n or Make) can be the right and cheapest answer, and we will tell you so. When the agent is core to your product — bespoke logic, real reliability targets, or data you cannot hand to a third party — we build a custom, instrumented agent you own outright.

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.

We instrument every call from day one. Per-customer cost dashboards, hard daily caps, automatic graceful-degradation when budgets are approached.

It depends on the surface area — a single well-scoped agent or RAG feature is a few weeks; a full product with evals, dashboards, and fallbacks is more. We start with a short paid discovery to pin the use case and data, then quote a fixed-scope build so there are no surprises.

Most first versions ship in 4–8 weeks: discovery, a working demo, then hardening (evals, cost/latency dashboards, human-in-the-loop fallbacks). We ship a usable demo early rather than disappearing for a quarter.