Support AI that reasons in the open.
Most support bots either lie confidently or punt everything to a human. TriageMind does neither — it resolves the routine, asks for proof when money's at stake, escalates the hard cases with a full briefing, and is honest about what it doesn't know.
- 6
- reasoning steps
- 3
- routing outcomes
- 0
- guardrail violations
“My order arrived dented and I'd like a refund — order #4821.”
Threshold 75% — clears (auto-resolve eligible)
Today's support bots fail in two ways. TriageMind fixes both.
Overconfident bots
Hallucinate wrong answers and promise things that break policy. They erode trust fast.
Useless-cautious bots
Forward every ticket to a human and save no one any time. Why bother?
TriageMind
Reasons step by step, knows when it's unsure, and hands humans a summary instead of a blank page.
Six reasoning steps you can watch
Every complaint runs through the same transparent pipeline, streamed live to a glass-box UI — so you always see why, not just the answer.
- Step 1
Understand
Pulls out the real issues, the customer's intent, and whether they're about to churn.
- Step 2
Classify
Tags severity, category, and sentiment so the right cases get the right attention.
- Step 3
Ground
Looks up your actual policy docs and cites the passages it relies on.
- Step 4
Decide
Scores its own confidence, then routes the case: resolve, request evidence, or escalate.
- Step 5
Draft
Writes a grounded, cited reply — or a clean briefing for the human taking over.
- Step 6
Self-check
Reviews its own draft against policy and fixes mistakes before anything ships.
One decision, three honest outcomes
Most bots only know how to answer or escalate. TriageMind has a third gear — it can ask for proof when a claim is risky, instead of guessing.
Resolve
Confident and on-policy. It sends a grounded, cited reply automatically — the routine work is done, no human needed.
Verify
A photographable damage claim worth real money? It politely asks for a photo first — framed as “help us find the cause,” not “prove it.”
Escalate
Unsure, high-severity, or a churn risk? It hands a human a full briefing — issues, severity, citations, and why — instead of a blank page.
Six things a friendly chatbot can't do
Each one targets a way ordinary support bots lose your trust.
Knows its limits
Every decision carries a confidence score. It only auto-resolves when confidence ≥ 0.75 and its self-check passes — otherwise it asks for evidence or escalates.
Catches its own mistakes
After drafting, it critiques its own reply against a checklist. If it slips, it rewrites and re-checks — up to twice — before anything ships.
Cites its sources
Answers are grounded in your real policy docs, and every factual claim links back to the passage it came from. No invented policy.
Takes real actions
It doesn't just chat. It calls tools — look up an order, check refund eligibility, open a ticket — so the routine work actually gets done.
Can't break policy
Hard guardrails stop it from promising off-policy refunds, inventing compensation, or making claims your knowledge base doesn't support.
Proves it works
An evaluation harness runs the agent over a labeled test set and reports measured accuracy — a real number, not a marketing claim.
Real agent infrastructure, not a wrapper
File Search grounding
Policy docs in a managed vector store — answers cite real passages.
Function tools
The agent calls live functions to look up orders and check eligibility.
Glass-box reasoning
Every step streams to the UI as it happens — nothing hidden.
See it think for itself.
Drop in a messy customer complaint and watch the six steps unfold in real time.
Try the live demo