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Insurance Assistant

Answers insurance product questions on Telegram from approved material, not guesswork

A Telegram assistant for an insurance and health-product line. It answers customer and agent questions about products, features and processes from an organised knowledge wiki built from approved brochures, PDFs and FAQs, so answers stay consistent and traceable.

TelegramProduct Q&AKnowledge wikiApproved sourcesMultiple AI models

At a glance

What it does01

Answers customer and agent questions about products, features and processes
Digests brochures, PDFs and FAQs once into structured, linked knowledge pages
Gives the same answer to the same question, across every agent and customer
Keeps a chat history for review
Can work with more than one AI provider, so we can choose the best model for cost and quality

Example conversation02

IA

Insurance Assistant

online

ClientDoes the critical illness plan cover early-stage cancer?

Insurance AssistantYes. According to the approved product brochure, the plan's early-stage illness benefit covers early-stage cancer. The payout and waiting period are listed in the brochure's benefits table. Would you like the claim steps?

ClientYes, how do I make a claim?

Insurance AssistantFrom the approved claims FAQ: send the claim form with the doctor's report and diagnosis, and the claims team will follow up. For anything about your own policy, I'll pass you to your adviser.

Illustrative example

Human vs agent03

Same taskAnswering one product question from brochures

By hand

≈ 15 minstaff time

Find the right brochure or FAQ
Search the PDF for the exact clause
Write a reply; colleagues may word it differently

With the agent

≈ 1 minstaff time

A customer or agent asks on Telegram
Agent answers from the approved wiki pages
Staff review the logged chats when needed

Answers in seconds, the same way every time

By hand

With the agent

Saves ≈ 93% of staff time

Estimates for one typical task, based on how the workflow runs. Actual results vary.

Ad-hoc AI vs our agent workflow04

The same task, done by prompting a general chatbot by hand versus through the agent’s set workflow.

Prompting a chatbot by hand

Tokens per task

Right first time

Whole brochures pasted in for every question
May answer from general knowledge, not your product
Different staff get different answers

Our agent workflow

Tokens per task

73% fewer

Right first time

Brochures digested once into linked wiki pages
Answers come only from approved material
Updating the wiki updates every future answer

No AI is 100% reliable. When a run fails, the agent retries automatically or hands it to a person.

Estimates for one typical task, based on how the workflow runs. Actual results vary.

How it works05

Step 1
Approved brochures, PDFs and FAQs are built into a wiki
Step 2
A customer or agent asks a question on Telegram
Step 3
The message pipeline routes it to the right wiki pages
Step 4
The AI model answers from that approved material
Step 5
The answer is sent back and the chat is logged

Why it's trustworthy06

Answers come only from approved product material
Updating the wiki updates every future answer at once
Answers can be traced back to the wiki page they came from

Good for07

Insurance, wealth and health-product teams
Agency networks that need consistent, compliant answers across many agents
Customer service teams handling repeated product questions

Read the case study

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