An Indian insurer was triaging motor claims by hand over five days. We put eight specialist AI agents on every claim — they read the photos in parallel, settle the obvious cases, and route only the hard ones to a human, each decision carrying a confidence score.
Claims run on speed and trust. A five-day wait costs goodwill; an opaque decision costs an audit.
Photos in, a triage decision out in about fifty seconds — the claim moves the moment it lands instead of sitting in a queue.
Assessors stop grinding through routine claims and spend their day on the genuinely ambiguous cases that need judgement.
Every recommendation comes with a confidence score, so a human can see exactly how sure the system is and why.
One agent reads damage from the photos, one prices parts, one estimates labour, one reads the policy, one checks for fraud — plus a reasoner and a reply agent, and an orchestrator that fuses them into a single recommendation with a confidence score. Below a confidence threshold it routes to a human, transparently.
The agents do the whole assessment, then route only what a human should touch.
The customer submits the claim with photos of the damage.
Specialist agents work in parallel — damage, parts, labour, policy and fraud, all at once.
It merges every signal into one recommendation plus a confidence score.
High confidence auto-decides; low confidence routes to a human, clearly flagged.
This isn't a black box replacing your assessors — it's how triage scales while people stay in control.
Routine, clear-cut claims clear automatically — the backlog stops building while intent and evidence are still fresh.
Assessor time goes where judgement matters — the ambiguous, disputed and high-value claims a machine shouldn't call alone.
Each call is traceable by its confidence score — and the same pattern reruns for KYC, health and FMCG.
That's where this triage architecture pays off. Let's talk about the outcome you need.