SofStack is an insurance AI MVP development company building AI products for insurers, brokers, MGAs, TPAs and insurtech companies.
Insurance runs on documents, rules and judgement: policies, submissions, claims and correspondence. AI can process much of this work faster and more consistently. We build insurance AI MVPs with the audit trails and human oversight a regulated business needs.
Who We Work With
Property and casualty insurers automating claims and underwriting
Life and health insurers speeding up applications and claims review
Brokers and MGAs processing submissions and comparing quotes
Third-party administrators handling high claims volumes
Insurtech companies adding AI to their platforms
Insurance AI MVP Use Cases
Use case | What the AI does | Business impact |
First notice of loss | Captures claim details by chat, email or forms | Faster claim intake |
Claims document processing | Extracts data from invoices, reports and photos | Shorter cycle times |
Claims triage | Scores complexity and routes claims to the right handler | Better handler allocation |
Fraud indicators | Flags unusual patterns for investigation | Lower leakage |
Submission intake | Reads broker submissions and fills underwriting systems | More quotes per underwriter |
Policy comparison | Compares wording and coverage across policies | Faster review and advice |
Customer service copilot | Answers coverage and claim status questions | Lower cost per contact |
Human Oversight and Explainability
Recommendations, not final decisions: handlers and underwriters approve outcomes
Reasons shown for triage scores, fraud flags and recommendations
Source references to the documents behind each extracted value
Audit trails of AI outputs, user decisions and overrides
Fairness checks where outputs could affect customers
Security and Data Protection
Encryption of policyholder and claims data in transit and at rest
Role-based access by line of business, region and team
Private deployment in your cloud environment
Data protection by design for GDPR, UK GDPR, CCPA and local insurance rules
Model choice for sensitive data: enterprise endpoints or self-hosted models
NDA and full IP transfer before work begins
Integration With Insurance Platforms
System | Examples |
Core platforms | Guidewire, Duck Creek, Sapiens, Majesco and in-house systems |
Document stores | SharePoint, ECM platforms and email inboxes |
CRM and service | Salesforce, Microsoft Dynamics, Zendesk |
Data platforms | Snowflake, Databricks, SQL warehouses |
How We Deliver Insurance AI MVPs
1. Workflow discovery with claims, underwriting, operations and IT teams.
2. Document and data review of real claims or submissions, with masking in place.
3. Proof of concept measured against current handling times and accuracy.
4. MVP build with integrations, review screens and audit trails.
5. Pilot on one line of business before wider rollout.
Insurance AI MVP Pricing
Engagement | Starting price | Timeline |
Discovery | From $2,500 | 2 weeks |
Proof of Concept | From $5,000 | 3–4 weeks |
Insurance AI MVP | From $20,000 | 10–14 weeks |
Dedicated AI Team | From $6,000/month | Monthly |
Pricing includes the audit, security and review workflows insurance operations require.
Frequently Asked Questions
Which insurance AI use case should we start with?
Claims document processing and submission intake usually show value fastest, because volumes are high and results are easy to measure.
Does AI make claims decisions?
In our MVPs, AI prepares data, scores and recommendations. Claims handlers and underwriters make the final decisions.
Can AI read photos and scanned documents?
Yes. We combine OCR, document AI and image analysis to process scanned forms, invoices and damage photos.
Can you integrate with Guidewire or Duck Creek?
Yes, through their APIs and integration frameworks. We confirm the options for your setup during discovery.
How much does an insurance AI MVP cost?
SofStack insurance AI MVPs start from $20,000, with a proof of concept from $5,000.
Build Your Insurance AI MVP
Tell us which claims or underwriting workflow you want to improve. We will propose an approach and a starting engagement.