4
Bot interfaces — Customer, Claims Assistant, Agent, Garage
Image + Audio
Multi-modal incident onboarding
AI
Predictive repair estimation from image recognition
QR
Invoice generation with e-payment or cash reconciliation
Core Workflow

One incident. Four roles. A single synchronised thread.

AI-Insure builds synergy between the four parties in every claim — replacing disconnected calls, forms, and follow-ups with a live, shared workflow state that each party sees through their own bot interface.

C
Customer
Reports the incident by image, text, or audio; receives estimates, updates, and pays through the bot.
CA
Claims Assistant
Notified instantly with full artefacts, reassures the customer, and tracks the case through resolution.
A
Agent
Reviews the predictive estimate, selects a garage against customer preference, and can override pricing post-inspection.
G
Garage
Receives the case with estimate, uploads work-in-progress images, and triggers invoicing on completion.
Onboarding & Fraud Prevention

From first message to a defensible estimate.

01
Multi-modal case onboarding
The Customer Bot accepts images of the incident alongside a text description and/or an audio snippet — capturing the full context of what happened in whatever format is fastest for the customer in the moment.
02
Image verification for fraud prevention
Submitted images are verified against the customer's registered vehicle, confirming the car in the claim is genuinely the insured vehicle before any estimate is generated.
03
Predictive repair estimation
AI image recognition assesses visible damage and produces a predictive repair value, cross-referenced against a live database of material pricing sourced from car material supplier agents.
04
Instant notification with artefacts
The Claims Assistant and Insurance Agent are notified of the incident immediately, with the full artefact set — incident video and audio — attached to the case.
05
Customer reassurance
The Claims Assistant engages the customer directly through the bot at first contact, reducing the anxiety and uncertainty that typically follow an accident.
Estimate to Fulfilment

Garage coordination, approval, and payment — without leaving the thread.

06
Agent bot notifies the garage
The Insurance Agent Bot passes the case to the selected garage complete with the predictive estimate, so repair work can be scoped before the vehicle even arrives.
07
Garage selection by customer preference
Garage assignment factors in the customer's stated preference, balancing convenience and trust against network and pricing considerations.
08
Price override after physical inspection
The agent can override the predictive estimate once a physical inspection has taken place, keeping the AI estimate as a starting point rather than a final word.
09
Customer confirmation of estimate
The final estimate is put back to the customer for confirmation through the bot before repair work proceeds.
10
Shared work-progress status
Progress updates flow to the customer, claims assistant, agent, and garage simultaneously through the bot — no single party is left chasing another for status.
11
Work-in-progress image upload
The Garage Bot uploads in-progress repair images directly into the case thread, giving every party visual proof of progress.
12
Invoicing with QR payment
On completion, an invoice is generated with a QR payment code and pushed directly to the Customer Bot.
13
Electronic or cash payment, with status tracking
Customers pay electronically through the bot or settle in cash, with payment status updated across the workflow either way.
Infrastructure & Governance

Built to sit inside your existing insurance infrastructure — not replace it.

AI-Insure is designed as an integration layer first. It maps onto your present claims workflow, optimises it, and connects into the systems, security policies, and infrastructure you already run.

Integration

Existing data pipeline API

Integrates directly with your present insurance company data pipeline via API, rather than requiring a parallel data store.

Integration

Manual capture fallback

Supports manual capture of records and images for cases or environments where automated intake isn't available.

Integration

Workflow mapping & transformation

Present insurance workflows are mapped to the AI application workflow, then transformed and optimised rather than discarded.

Data

Ontological data reference

Multi-modal artefacts — images, audio, video, text — are linked through an ontological reference layer with defined relationships, integrated into the LLM context.

AI

Model-agnostic routing

A context-switching router keeps the platform model-agnostic, optimising token usage across whichever underlying models are in play.

Security

Governance & Active Directory

Enforces security policy validation and ACL rules under an AI governance framework, with seamless integration to Microsoft Active Directory.

Platform

Kubernetes-native scale-out

Hosted on a containerised, Kubernetes-based architecture built to scale out as claim volume grows.

Platform

Infrastructure integration

Deploys into your present insurance company infrastructure setup rather than demanding a greenfield environment.

Interface

Multi-modal bot interface

A single conversational interface pattern — text, image, audio, video — consistently applied across all four role-based bots.

See AI-Insure mapped onto your own claims workflow.

We'll walk through how the platform integrates with your existing data pipeline, infrastructure, and governance requirements.