Autonomous agents and automated pipelines that handle customer queries, outreach, operations and data work around the clock — with guardrails, retries, and a human in the loop where it matters.
A real agent doesn't take breaks. Here's a typical 24 hours of one running in production — every line is work that used to need a person.
An agent is a piece of software that can read, decide and act on its own — like a tireless junior teammate who follows your rules exactly and asks for help when unsure.
The difference between AI that wows in a demo and AI you can trust in production is everything around the model. This is that everything.
A test suite scores every change before it ships — so quality is measured, not hoped for.
Anything high-stakes pauses for a person to approve. The agent knows what it shouldn't decide alone.
When something fails it retries, then routes to a human — it never silently drops work.
Every action is logged and visible on a dashboard. You always know what it's doing and why.
Guardrails, structured outputs, an evaluation suite, and human approval on anything high-stakes. We design the failure paths as carefully as the happy path — the agent escalates instead of guessing.
Whatever fits the job and budget — frontier models where quality demands it, smaller or open models where they're enough. You're never locked to one provider.
Yes. It reads your documents and systems through retrieval with access controls and citations, so answers are grounded and traceable — and sensitive data stays where it belongs.
It escalates to a human with full context instead of making something up. 'I don't know, here's who should' is a designed-in behaviour, not a failure.
We'll find the highest-leverage thing to automate first — free, in a two-week audit.