Applied AI, Not Aspirational AI
Insurance and BFSI operations are document-heavy, rule-bound and deadline-driven. That is exactly where applied AI pays for itself. We use AI in two distinct ways: inside our products, where it reads, extracts and assists at scale — and inside our engineering process, where it makes what we ship better designed, better tested and more secure.
In Our Products
Policy copies, endorsements, claim files and KYC documents arrive as scans, photos and PDFs. Our OCR pipelines convert them into structured, validated data — and policy recognition models identify the document type, insurer format and key fields before a human ever opens the file.
Natural language is how customers actually ask for things. We build conversational journeys that understand intent and resolve queries without a ticket — and route the rest to the right person with context attached.
Where judgment at scale is the bottleneck, models assist — and people decide. Every AI-assisted output passes through the same maker-checker controls as manual work.
We are deliberately multi-model: the right model for the task, the data-sensitivity and the cost profile — never one vendor for everything.
In Our Engineering Process
We use Anthropic's Claude across our software development lifecycle. The result is not faster slideware — it is systems that are better designed, better tested and harder to break.
Claude works alongside our engineers from the first design conversation onward.
Every change is challenged before it ships — by people and by AI trained to find what people miss.
Governance
In regulated industries, "the model did it" is not an answer. Our AI features run inside the same controls as the rest of the platform.
AI drafts, extracts and flags; people approve. Maker-checker applies to AI-assisted outputs exactly as it does to manual entries.
Every AI-assisted action is logged with its inputs and outcome — the same audit standard IRDAI-ready reporting demands everywhere else.
Model choice follows data sensitivity. Where client data cannot leave the environment, we deploy self-hosted models instead of external APIs.
Talk to us about where automation and AI genuinely fit your operation — and where they don't.
Start a Conversation