Overview

Polivra is a US insurtech platform, and its team was buried in policy review. Policies came in every day from dozens of carriers, and someone had to open each one, check it against the coverage rules, and decide whether it passed. That was fine at low volume. As it grew, the checks got slow and results varied from one reviewer to the next. Sureloop wanted software that could read any policy, clear the clean ones by itself, and pull in a human only when a policy needed a second look. Every call also had to be traceable for compliance.

Technologies Used

Python
FastAPI
Reactjs
PostgreSQL
AWS
LangChain

Project Highlights

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Zero-Touch Policy Review Pipeline Launched

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Confidence-Scored Document Extraction

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Rule-Based Coverage Validation Engine

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Rule-Based Coverage Validation Engine

The Challenges

1

Policies came in from many carriers. No two looked alike. Some were clean digital PDFs, others were scanned copies with odd layouts, stamps, and handwriting. The app had to read every one and pull the same fields.

2

Clearing a policy with no human review means the app has to be right. A missed limit or wrong expiry date could let a bad policy through, so we had to define when skipping review was safe.

3

Insurance runs on audits. It was not enough for the app to say a policy passed. Compliance and auditors needed to see which fields were read, which rules ran, and why the app cleared or flagged it.

4

Polivra runs a live product with real users, so the checks could not slow anything else down. The app had to work through thousands of policies in the background while the rest of the platform stayed responsive.

Solutions by Bacancy

1

We built the first piece to read policy documents, whether clean PDFs or crooked, poorly scanned copies with rubber stamps. It accurately pulls out coverage type, limits, dates, named insured, and endorsements. With our insurance app development services, our team carefully trained it on real carrier documents, so it gets the fields exactly right even when a scan is a total mess.

2

Once a policy is read, it goes through a rule engine that already knows what the account requires. Built with our insurance IT services, the engine lines the policy up against those rules and looks for the usual problems, like a limit that falls short, a lapsed date, or a missing endorsement. If nothing is off, the policy clears. If something is, it goes to a reviewer with the reason attached.

3

We did not want the app clearing policies it was unsure about, so every field carries a confidence score. Our Python developers designed the backend logic so a policy clears only when the reading is reliable and every rule passes. If a field looks uncertain or a rule falls into a gray area, the policy is sent to a reviewer instead of relying on guesswork.

4

Every check writes down what happened as it runs. You can open any policy and see which fields were pulled, how confident the app was on each one, which rules ran, and what each rule returned. When compliance or an auditor asks why a policy passed or got flagged, the answer is right there in the record, start to finish.

Core Features

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Automated Policy Document Reader

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Coverage Rule Validation Engine

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Confidence-Based Auto-Clearing

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Exception Flagging With Audit Logs

No. of Resource

04

No. of Resource

Time Frame

April 2025 - August 2025

Time Frame

Project Snapshot

Outcomes

10,000 policy checks cleared automatically with zero manual reviews across all carriers.

3x faster policy turnaround for the ops team after launch.

100% of decisions backed by a clear, step-by-step audit trail.

12+ carrier formats handled with one consistent set of checks.

40% lower review workload even as policy volume kept growing.

2x faster onboarding of new policies into the live platform.

Technical Stack

Frontend React
Backend PythonFastAPI
Database PostgreSQL
Document Processing AWS Textract (OCR)
AI Orchestration LangChain with LLM-based extraction
Cloud Infrastructure AWS
Architecture Microservices & Containers
API Communication REST APIs
Project & Issue Tracking Jira

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