Every agent change runs against a regression suite before it ships, and every production run is traced end to end, so we can show it works instead of just claiming it.
Shipping an agent change without evidence that it still behaves correctly is how small changes cause big incidents. We build a regression suite that runs on every change, policy guardrails that block out-of-scope actions before they execute, and full tracing so a production run can be replayed and audited.
Signs it's worth a conversation.
A clear path from idea to production.
We map where this actually pays off in your workflow, not just where it's technically possible.
We design the approach around your systems and data, not a generic wrapper bolted on top.
We build it with evals, tracing, and human-handoff points from day one, not added after something breaks.
We ship into production, watch how it performs, and iterate against evidence, not guesses.
Agent behavior changes are treated like any other production code change, with evidence attached:
The things people ask us before starting a project like this. If yours isn't here, ask us directly, we reply like humans.
Ask us anything→A regression test suite runs automatically on every change and has to pass before the change reaches production, turning "it seemed fine in testing" into a specific, reviewable record.
Policy guardrails block actions outside the agent's approved scope, enforced before a tool call executes, not after the fact, so an out-of-scope action never actually runs.
Yes, every step, plan, tool call, and result is logged for audit and debugging, so a production run can be replayed end to end rather than reconstructed from memory.
It's the opposite in practice: a regression suite catches breakages before they reach production, which means changes ship with confidence rather than everyone holding their breath after a release.
They're routed for human review before they affect a real customer, based on policy rules or a confidence threshold, rather than being allowed through and hoped for the best.
The gap between an agent demo and an agent in production is almost always evidence: can you show that this specific change didn't break the other twelve things it used to do correctly? A regression suite and a trace log turn a vague sense that it seemed fine into a specific, reviewable record, which is what actually earns the confidence to let an agent touch a real customer or a real transaction.
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