Why We Built Our Own Insurance AI Bot — And What It's Doing Now
The Problem We Kept Running Into
Running retention and revival campaigns at scale means making a lot of calls. The economics only work if human callers spend their time on conversations that actually need a human — convincing, explaining, handling objections - Not on the 60–70% of attempts where the customer doesn't pick up, isn't ready, or needs basic information first.
The obvious answer was a voice bot for warm-up. We tried several. Every one of them hit the same wall: generic insurance conversations that customers saw through immediately. Off-the-shelf bots aren't trained on how Indian policyholders actually talk about their policies — the hesitations, the specific questions about fund value or premium dues, the moment a customer is close to converting.
We had something those vendors didn't: 5 lakh+ real insurance customer conversations from our own managed services operations, and the ability to generate policy-specific benefit projections through our Content Engine!
So we built InsureBot ourselves.
What InsureBot Does
InsureBot handles first contact across large customer bases — warming up leads, collecting intent signals, and scheduling callbacks for human agents. It's trained on real insurance conversations, understands policy-specific context, and can reference actual benefit figures during a call.
Where fixed IVR blasts sent the same message to everyone, InsureBot has a conversation.
Human callers take over on warmed-up leads — spending their time where it counts.
The Impact
- 15–25% improvement in process productivity from human + bot combination vs. human-only operations
- Higher revival collection rates compared to traditional IVR-based outreach
- Infrastructure cost under 50% of an equivalent human caller setup
- Clients are charged on results — not on bot usage
InsureBot is now being evaluated by insurer clients for independent deployment — moving from an internal capability to a standalone product.
