Case studies

AI agents, working inside real businesses.

Our featured case study comes first. Below it are two illustrative scenarios that show other patterns we typically see in mid-sized businesses.

Featured case study

A mid-sized insurance brokerage in Mumbai

3x businesswith the same headcount

A mid-sized insurance brokerage in Mumbai generated 3x business with the same headcount, using AI agents that assist in CRM, placements, servicing, claims processing and growth.

Challenge

An insurance brokerage lives on relationships, follow-ups and paperwork. As business grows, the usual answer is to hire more people for every client, policy and claim. The goal was to grow much faster without growing the team.

Solution

We deployed AI agents that assist the existing team across the full life of an account, from the first enquiry to renewals and claims. People stay in charge of relationships and judgement, while the agents take on the repetitive work around them.

Outcome

3x business with the same headcount. The same team now handles three times the volume of work, with agents supporting every stage.

Where the agents help

CRM

Keeps client records complete and current, logs interactions, and reminds the team who needs a call or follow-up and when.

Placements

Prepares submissions and compares insurer options so the team can place business faster and with confidence.

Servicing

Handles routine client requests, documents and renewals, so service stays responsive as the book grows.

Claims processing

Organises claim documents, checks them for completeness and tracks progress, helping claims move forward with less back and forth.

Growth

Surfaces cross-sell and referral opportunities in the existing book and supports outreach, turning relationships into new business.

The client is not named here. More detail is available on request.

Illustrative scenarios

Other patterns we see.

The two scenarios below are illustrative. They describe typical engagement patterns and are not stories about named clients, and they contain no results. More real client stories are coming, and are available on request.

Illustrative scenario

Document-heavy back office for a mid-sized manufacturer

Purchase orders, invoices, quality certificates and delivery notes pile up as PDFs, scans and emails, and are re-typed into systems by hand.

What we would build: A fine-tuned open source model, running in the company's own environment, that reads documents, extracts the key fields, matches them against records and routes exceptions to a person.
What changes: Less re-keying, fewer errors, and a clear audit trail, while sensitive documents stay under the company's control.

Illustrative scenario

Multilingual sales assistant for a retail chain

Customers ask about products, availability and offers in Hindi, English and regional languages, and store teams cannot answer every query quickly.

What we would build: A sales assistant grounded in the product catalogue and store stock, comfortable in several languages, that captures interested customers and passes them to the right store.
What changes: Customers get helpful answers in the language they prefer, and store staff spend their time on conversations that are ready to convert.

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