For teams that need agents to do real work, not demos
Agents that do the work autonomously — not a copilot you babysit.
What this fixes
Most "AI agents" are chatbots in disguise — they reply, but they don't do anything. They hallucinate on your data, keep no memory of what they did, and have no guardrails when an action carries real risk, so they never make it past a demo into production.
- 01
Replies, not results
A chatbot answers a question; you needed the task actually done.
- 02
Confidently wrong
Ungrounded models invent answers your customers and staff then act on.
- 03
No guardrails, no trust
Without evals, oversight, and fallbacks, no one will let it touch production.
We build agents that research, decide, and act — grounded in your data, measured against evals, with a human in the loop wherever it matters.
Grounded in your data
Retrieval on your own content keeps answers accurate and current, not invented.
Measured, not eyeballed
An eval harness scores output against a golden set before and after every change.
Oversight where it counts
Approval gates, fallbacks, and observability on every action that carries risk.
Everything in the engagement
Agents that complete tasks
Multi-agent systems that do real work end to end, with guardrails — not a chatbot that just replies.
Grounded in your data
Retrieval-grounded (RAG) on your own content, so answers stay accurate and current.
Reliability engineering
Evals, observability, fallbacks, and human-in-the-loop so you can trust it in production.
Improves with use
Built to run live and get sharper as it sees more of your real traffic.
What teams get
- 0%
- of tier-1 tickets auto-resolved by a support copilot
- 0 weeks
- from kickoff to a grounded agent in production
- 0+
- vetted senior engineers on call
From first call to first release in weeks
A Pod embeds in your stack, narrows the work to the metric that matters, and ships the smallest system that moves it.
- 01
Scope the outcome
We pin the metric that matters and what "done" means — before any code.
- 02
Stand up a Tuned Pod
A senior engineer steering a proprietary in-house agent harness (Claude, Codex, Gemini), embedded in your stack within days.
- 03
Build & ship
A working system in front of real users in weeks — the agents do the building; our engineers own every call that carries risk.
- 04
Measure & improve
We track the number it moves and sharpen it as your data and the models change.
Built on what you already run
FAQ
- How is this different from a chatbot?
- A chatbot replies; our agents research, decide, and act — completing tasks end to end, with oversight where it matters.
- How do you stop it hallucinating?
- Retrieval-grounding on your data plus an eval harness and guardrails, so output is measured against a golden set, not eyeballed.
- Can a human stay in the loop?
- Yes — approval gates and human-in-the-loop are built in for any action that carries risk.
- Is it production-ready or a demo?
- Production-ready: observability, fallbacks, and evals are part of the build, so it holds up under real use.
Tell us the outcome you need.
Book a 30-minute call. We’ll map the highest-impact system to build first — and what moving that number is worth.