AI workflow integration

LLMs and automation wired into real business processes, not demos — with the evaluation, guardrails, and fallbacks that keep them useful in production.

What it covers

Connecting models to the systems where work actually happens: inboxes, tickets, documents, internal tools. We design the evaluation harness, the guardrails, and the fallback path for when the model is wrong.

How an engagement runs

We pick one workflow with a measurable cost, build the thinnest working version against real examples, and measure failure modes before scaling. Automation earns trust incrementally or it gets switched off.

What you get

A working integration plus the harness around it: evaluation sets, guardrails, fallback behavior, and documentation your team can extend as the workflow changes.

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