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AI software & agents

Production AI, not another proof of concept.

We build agents, retrieval systems, and AI features that ship. That means real integrations with your stack, evaluation suites that catch regressions, and guardrails that keep behavior predictable once live traffic hits.

agent · run #4f2a
plan → resolve customer intent
search_docs("refund window")
retrieve · 4 chunks · score 0.92
guardrail · grounded ✓
answer drafted · cited 2 sources
passed evalslatency 1.2s · $0.004

What is included

01

Autonomous agents and tool-use workflows

02

RAG and retrieval over your own data

03

LLM features wired into existing products

04

Evaluation suites, tracing, and guardrails

05

Model and prompt cost and latency tuning

The result

AI that behaves the same in production as in the demo

A system your engineers can extend

Clear metrics on quality, cost, and latency

Best fit

Teams moving an AI prototype toward launch

Products that need an agent or copilot built right

Companies with data but no in-house ML team

Next step

If this is what you are building, start the brief and we will scope the route.

Start a build