Quality control for AI agents.

Monte sits between your agent and your users, catching wrong replies before anyone sees them.

See how it works

An agent that looks right can still be wrong.

Without Monte
Customer sees the error
Agent says
You are eligible for a refund within 60 days. Free returns are included.
Sent straight to the customer
Customer reads the wrong answer
Mistake found, too late to take back
With Monte
Customer is protected
Agent says
You are eligible for a refund within 60 days. Free returns are included.
Sent straight to the customer
Monte spots 1 unsupported claim
Routed to a teammate before delivery

See it on your own answer.

Paste an agent answer and the source notes. Monte will tell you what's supported, what's risky, and what to do next.
Try a sample:
You
Agent
Monte
1
Eligible for a refund within 60 days
Source says 30 days, not 60.
2
Premium customers get free shipping on returns
Not mentioned in sources.
3
Premium has a dedicated support line
Sources mention priority support routing.
Confidence 0.45 · low
Route to human

FAQ

Monte checks agents before they are shown to users. It reads each answer, compares it to your sources, and returns a clear decision your product can act on.

No. Your model still creates the answer. Monte sits between the answer and the user, and helps you decide whether the answer is safe to send.

Support replies, summaries, RAG answers, and other user-facing AI outputs. Anywhere an AI generates text that a person will read or act on.

Your product decides. Monte returns a structured result with confidence, flagged lines, and a recommended action. Your code can block the answer, retry, rewrite, send with a warning, or route to a human.

No. Monte is built so you only review what actually needs a human. Most answers go through cleanly; the small risky tail gets the attention it needs.

Stop bad answers.

Monte checks every reply your agent writes and flags what isn't supported, before a user ever sees it.