Policy extraction software for scanned insurance documents

Jul 5 – Oct 26, 2026Updated Oct 26, 2026Reviewed by

How we measure

Which brands AI mentions

#BrandMentioned in
#1tiedPerfectParser51%
#1tiedParsli41%
#3tiedParseCheck33%
#3tiedInsuranceOCR31%
#3tiedInsurGrid31%

Mentioned in

ChatGPTChatGPTGoogle AI ModeGoogle AI Mode

Widest split: PerfectParser, 92% on ChatGPT and 8% on Google AI Mode.

  • #1tiedPerfectParserChatGPT 92%Google AI Mode 8%
  • #1tiedParsliChatGPT 44%Google AI Mode 38%
  • #3tiedParseCheckChatGPT 60%Google AI Mode 4%
  • #3tiedInsuranceOCRChatGPT 48%Google AI Mode 13%
  • #3tiedInsurGridChatGPT 12%Google AI Mode 50%

Questions and answers

  • Google AI ModeOct 26, 2026

    1. 1Sensible
    2. 2Indico Data
    3. 3Indico Data IDP for P&C Insurance
    4. 4Hyperscience
    5. 5SortSpoke
    6. 6Reducto

    Extracting complex, unstructured information—such as policy limits, endorsements, exclusions, and named insured details—from scanned insurance documents requires Intelligent Document Processing (IDP) platforms that combine optical character recognition (OCR) with machine learning and large language models (LLMs).

    According to insurance workflow and insurtech industry evaluations, several specialized platforms handle this multi-layered data extraction:

    • Sensible (Sensible Insurance Document Extraction ) uses a hybrid approach pairing OCR with layout-based rules and LLM parsing to target complex text blocks, declarations pages, and exclusion provisions, converting them cleanly into structured JSON data.
    • Indico Data (Indico Data IDP for P&C Insurance ) focuses heavily on enterprise-grade underwriting intake, submissions, and policy servicing, using machine learning to parse unstructured carrier forms, endorsements, and policy text.
    • Hyperscience (Hyperscience ) provides enterprise automation and AI-driven document processing designed for large carriers to ingest, classify, and extract deeply buried data points across varied departmental formats.
    • SortSpoke (SortSpoke ) targets commercial and excess & surplus (E&S) lines, allowing underwriting teams to configure their own custom extraction models for unstructured documents like complex policy jackets and endorsements.
    • Reducto (Reducto ) functions as an API-first document parsing utility well-suited for engineering teams needing to extract dense text and tricky tables from messy scanned PDFs.

    If you'd like, I can provide more details on:

    • The difference between rule-based OCR versus LLM-hybrid extraction for legal/exclusion text.
    • How these tools map extracted data directly into an Agency Management System (AMS) or Policy Administration System (PAS).

    Let me know what your specific tech stack or document volume looks like!

    Sources cited in this answer5

    ChatGPTOct 26, 2026

    1. 1V7 Go
    2. 2ParseCheck
    3. 3DocuOCR
    4. 4Excluria
    5. 5PolicyIQ Extract
    6. 6Uptiq Document AI

    For extracting policy limits, endorsements, exclusions, and insured details from scanned insurance documents, the strongest options are insurance-specific AI document extraction tools. They combine OCR or document vision with insurance-language analysis to turn scanned PDFs, declarations pages, and full policy packets into structured data.

    Best tools to evaluate

    • AI Agents for Insurance Underwriting and Claim Processing

    1. V7 Go

    (Best for full-policy analysis)

    Extracts policy limits, sublimits, deductibles, named insureds, endorsements, and exclusions across policy documents. Particularly relevant when you need to analyze how endorsements change coverage, not merely capture fields.

    Website:

    • poliza.tech — Plataforma InsurTech para empresas

    2. Excluria

    Best for brokers reviewing commercial policies. Extracts coverage limits, sublimits, exclusions, deductibles, and renewal information, with structured summaries and multi-policy comparisons.

    Website:

    3. ParseCheck

    Best for structured extraction and coverage-gap reviews. Extracts insured and carrier details, limits, deductibles, sublimits, exclusions, and endorsements, with outputs such as Excel and JSON.

    Website:

    • Azure Document Intelligence vs Textract vs Google Document AI | DocuOCR

    4. DocuOCR

    Best for high-volume scanned-document intake. Handles scans, faxes, photos, insurance policies, declarations pages, ACORD forms, and loss runs, with structured extraction and cross-document validation.

    Website:

    • Eagle-Eye | The AI-Powered Policy Reader | PermuteHQ

    5. PolicyIQ Extract

    Best for broker and insurer workflows. Converts scanned PDFs, photographed documents, policy schedules, and proposal forms into structured, validated data, with API connectivity for downstream systems.

    Website:

    • No-Code AI Agent Platform | AI Apps Development Platform for Financial Services - Uptiq

    6. Uptiq Document AI

    Best for lender and collateral-insurance reviews. Extracts named insureds, property coverage limits, per-peril sublimits, deductibles, mortgagee and loss-payee endorsements, and exclusion language.

    Website:

    Quick comparison

    ToolLimits & sublimitsEndorsements & exclusionsScanned documentsStructured output
    V7 GoYesYesBroad document supportYes
    ExcluriaYesYesPolicy PDFsSummaries, exports
    ParseCheckYesYesPDF and scanned documentsExcel, JSON
    DocuOCRYesDocument extractionScans, faxes, photosStructured records
    PolicyIQ ExtractPolicy dataPolicy data extractionScans, PDFs, photosValidated data, API
    UptiqYesYesFull policy documentsStructured records

    Capabilities are based on vendor-published descriptions; independently benchmark accuracy before choosing.

    What matters most for your use case

    For reliable extraction, prioritize these five capabilities:

    • Full-document OCR: Reads image-only PDFs, skewed scans, and low-quality copies.
    • Endorsement interpretation: Identifies form numbers and wording that modify the base policy.
    • Exclusion analysis: Captures exclusions and exceptions rather than just listing headings.
    • Source traceability: Links each extracted field to its source page and text.
    • Validation and review: Flags unreadable fields, conflicting limits, and uncertain interpretations for human verification.

    My recommendation: Start by comparing V7 Go, ParseCheck, and DocuOCR. They represent three useful approaches: deeper policy analysis, structured coverage extraction, and high-volume document processing.

    One important distinction: extracting an exclusion is not the same as determining its legal effect. Have a qualified reviewer verify material coverage conclusions.

    Would you like to explore tools with APIs and JSON output or tools for scanned commercial property policies?

    Sources cited in this answer14

  • Google AI ModeOct 15, 2026

    1. 1ParseCheck
    2. 2Patra Policy Checking
    3. 3Parseur
    4. 4Indico Data
    5. 5Hyperscience
    6. 6InsuranceOCR

    Parsing complex, multi-page scanned insurance policies—including declarations, endorsements, and dense exclusion schedules—requires specialized AI-driven Intelligent Document Processing (IDP) and policy-checking platforms.

    Software solutions capable of handling insured party details, limits, endorsements, and exclusions are categorized below by their primary use case:

    Dedicated Policy Checking & Coverage Extraction

    • ParseCheck : Specifically built for automated policy coverage extraction and certificate of insurance (COI) compliance validation. It parses carrier documents to pull policyholder data, specific limits, deductibles, sublimits, exclusions, and endorsements into structured outputs.
    • Patra Policy Checking (AI-Enabled) : Combines automated AI/ML document extraction engines with structured workflows designed to process commercial lines of business. It reviews policy headers, exposures, form schedules, limits, and endorsements against extensive validation checklists.
    • Parseur : Utilizes AI-powered OCR tailored for insurance workflows to capture data from coverage reports, policyholder details, and insurer specifications without relying on rigid, carrier-specific templates.

    General Enterprise Insurance IDP & Unstructured Data Platforms

    • Indico Data : An enterprise-grade unstructured data platform heavily used by commercial carriers and brokers to ingest complex, messy documents like policy forms, binders, and submissions.
    • Hyperscience : An hyper-automation and IDP platform that handles degraded scans, handwritten notes, and complex multi-page structured/unstructured insurance documents, extracting line-item policy specifications accurately.
    • Insurance OCR : Contextual AI-based extraction designed to read policies, endorsements, binders, and ACORD forms regardless of which carrier issued the document or how the layout deviates.

    If you can share what volume of documents you plan to process monthly and whether you need this integrated into a specific Agency Management System (AMS) or CRM , I can help narrow down the ideal platform fit.

    Sources cited in this answer4

    ChatGPTOct 15, 2026

    1. 1V7 Go
    2. 2PerfectParser
    3. 3BeCovered.ai
    4. 4DocuPipe
    5. 5Uptiq Document AI

    For your use case, I’d focus on insurance-specific document AI rather than basic OCR software. The key distinction is whether a platform simply reads scanned PDFs or can interpret the full policy—including declarations, coverage limits, exclusions, endorsements, and named insureds—and return structured data your team can verify.

    I found several products worth evaluating, ranging from ready-to-use policy parsers to enterprise AI tools that can integrate with underwriting, claims, and broker workflows.

    Best software options to evaluate

    • AI in the Insurance Industry: Trends and Predictions

    1. V7 Go

    (Full policy analysis)

    Designed for brokers, underwriters, and risk managers reviewing complete policy documents. It identifies limits and sublimits, exclusions, endorsements, named insureds, and conditions; it also supports policy comparisons and question-answering with cited policy evidence.

    Best for: Complex policies where understanding how endorsements change coverage matters.

    Visit V7 Go

    • Brokers

    2. PerfectParser

    Focuses on insurance document OCR and field extraction, including policyholder, carrier, coverage limits, deductibles, exclusions, and endorsements. It advertises template-free processing and exports to CSV, Excel, and JSON.

    Best for: Turning batches of policy PDFs into structured datasets without extensive setup.

    Visit PerfectParser

    • Brokers

    3. BeCovered.ai

    Built around broker workflows, including extracting limits, deductibles, exclusions, endorsements, and dates into Excel-ready fields. It also describes declaration-page extraction and comparisons between renewal terms.

    Best for: Brokerages and account-management teams that need consistent policy summaries and renewal comparisons.

    Visit BeCovered.ai

    • Document Extraction: From Unstructured to Structured Data (2026 Guide)

    4. DocuPipe

    An API-oriented option that converts insurance policy documents into structured fields, including insured parties, carriers, policy terms, limits, deductibles, and endorsements.

    Best for: Organizations building extraction into an existing claims, underwriting, or policy-management system.

    Visit DocuPipe

    • Intelligent Document Extraction Tool for Insurance

    5. Uptiq Document AI

    Extracts declarations-page limits, sublimits, named insureds, mortgagee and loss-payee endorsements, and exclusion language. Its documented focus is particularly relevant to collateral insurance review and financial institutions.

    Best for: Lenders, banks, and teams checking insurance adequacy for financed assets.

    Visit Uptiq

    How they compare

    CapabilityV7 GoPerfectParserBeCovered.aiDocuPipeUptiq
    Extract policy limitsYesYesYesYesYes
    Identify exclusions and endorsementsYesYesYesYesYes
    Capture insured-party detailsYesYesYesYesYes
    Compare policies or renewalsYesNot its main focusYesCustom workflow potentialCoverage adequacy focus
    Structured data / integrationEnterprise workflowsCSV, Excel, JSONExcel-readyAPI-orientedFinancial-system workflows
    Main fitPolicy reviewBulk extractionBroker operationsCustom integrationLender operations

    This comparison is based on the vendors' published capabilities, not independent accuracy testing.

    What I would test before buying

    Scanned policies introduce challenges that ordinary PDF extraction can miss. Ask each vendor to process a representative sample of your actual documents, including poor-quality scans and long endorsement schedules.

    Check for these six requirements:

    • Limits: Per-occurrence, aggregate, sublimits, and deductibles, with the correct coverage type.
    • Exclusions: Exact clause text, not merely an AI-generated summary.
    • Endorsements: Form number, edition date, amended coverage, and the provision being modified.
    • Insured parties: Named insured, additional insured, certificate holder, and other relevant parties kept distinct.
    • Source traceability: Every extracted value linked to the original page and preferably the supporting text.
    • Validation and export: Confidence indicators, human review, exception handling, and export to your required format.

    Do not rely on a vendor's advertised accuracy percentage alone. Test field-level accuracy on your own policies, especially whether the system misses an exclusion or incorrectly treats an endorsement as granting coverage. Have qualified staff verify substantive coverage conclusions.

    To narrow this down to the best fit

    One detail would help most: what kind of insurance documents are you processing?

    1. Document type

    Full commercial policies, including endorsements and exclusions

    Certificates of insurance (COIs / ACORD forms)

    Policies used for claims or legal coverage analysis

    A mixture of policy types and insurance documents

    2. Approximate processing volume

    Under 100 documents per month

    100–1,000 per month

    Over 1,000 per month

    3. Preferred output

    Excel or CSV spreadsheets

    JSON or API integration

    Direct integration into an existing system

    A searchable dashboard with source-page citations

    4. Deployment preference

    Cloud software

    Private cloud or on-premises

    Flexible; depends on security and cost

    [Compare suitable vendors]

    Sources cited in this answer6

Also asked as

  • What insurance document processing tools are capable of automatically extracting data like insured details, policy limits, exclusions, and endorsements from scans?