We’re an AI agent development company that ships agents with evaluation suites, guardrails and human review on the decisions that matter. Because the model will be wrong, and the system has to catch it before your customer does.
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They work in the demo.
The demo uses clean inputs, a cooperative user and a happy path. Production has none of those. It has the malformed record, the user who asks something nobody anticipated, the API that changes without notice, and the month-end edge case that exists twelve times a year.
An agent without evaluations has no idea it’s failing. An agent without guardrails fails expensively. An agent without human review on high-stakes decisions is a liability with a chat interface.
That’s not an argument against building agents. It’s an argument for building them properly.
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AI writes a great deal of the code. A senior engineer decides what’s correct.
We start by defining what “wrong” means for your use case, because you cannot guard against a failure you haven’t named. Then we build the eval suite before the agent, so there’s a scoreboard from day one. The agent is built against it, and we ship when the numbers clear the bar you set — not when the demo looks good.
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A concept build that makes the eval-first method inspectable: six static checks on an n8n export, a quality bar declared before results exist, regression diffs between versions, capped and labelled AI analysis — and a human gate on what enters the graded suite.
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Proof of concept from $35,000
Full pricing, what's included and what isn't — see pricing
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Agents drift. Models get deprecated, your data changes, and prompts that worked in March stop working in September. Automation-as-a-Service from $500/month covers monitoring, eval re-runs and iteration.
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Thirty minutes with the engineer who'd own the build. No pitch, no deck. Bring the problem; we'll tell you whether it's worth solving and roughly what it costs.
Book a build review