Alice Labs builds AI agents for insurers: claims processing from intake to payout in minutes instead of weeks, underwriting automation that evaluates risk 10x faster, and fraud detection that catches complex schemes rule-based systems miss. Deployed securely, built for GDPR and Solvency II requirements.
An experienced team with broad AI and tech backgrounds from leading companies
Linus
Co-founder & AI Consultant
Alice
CEO & Co-founder
Jens
AI Consultant
Eric
Co-founder & AI Consultant
Lisa
Project Lead & Implementation
Production-grade AI delivery, EU-native, senior team
Verified outcomes from completed AI implementations
Ljusgårda (Supernormal Greens)
Public Sector
Media Company
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Where AI agents deliver the highest ROI for insurers today
From intake to payout, AI agents handle the entire claims lifecycle. They extract data from photos and documents, validate coverage, score fraud risk, calculate payouts, and route complex cases to human adjusters with pre-built case files. Simple claims are resolved in minutes, not weeks.
Key Deliverables:
AI agents collect and analyze data from dozens of sources — financial statements, IoT sensors, telematics, public records — to produce risk assessments in minutes. Underwriters get AI-prepared summaries with risk scores, comparable cases, and pricing recommendations.
Key Deliverables:
AI detects sophisticated fraud patterns that rule-based systems miss: organized fraud rings, staged accidents, inflated claims, and identity fraud. By analyzing behavioral patterns, claim histories, and network connections, AI catches 30-50% more fraud with fewer false positives.
Key Deliverables:
| Process | Before AI | After Alice Labs |
|---|---|---|
| Claims Processing | 7-14 day cycle | Minutes for simple claims |
| Underwriting Review | 3-5 days per application | 30 minutes AI-augmented |
| Fraud Detection | Rule-based, high false positives | AI pattern analysis, 40-60% fewer FPs |
| Customer Onboarding | 2-3 days paper process | 15-minute digital flow |
| Regulatory Reporting | Weeks of manual compilation | Auto-generated, audit-ready |
Let's discuss your AI journey
Our team will help you prioritize use cases and build a concrete roadmap.
Alice Labs delivers AI agents across every major industry vertical
"We decided early on to embrace AI technology and needed a partner who could explore opportunities, propose solutions, lead change management, and build them. With Alice, we got everything in one place and have implemented multiple solutions that increased efficiency so significantly that an entire team could be reallocated."
Andreas Wilhelmsson
CEO & Co-founder
Supernormal Greens / Ljusgårda
"Alice Labs' AI training gave us all a real aha-moment, whether we were completely new to the field or experienced! The training contained a perfect balance between theory and practice. We have definitely become more efficient at work!"
Åsa Nordin
IT Manager
Trollhättan Energi
"The collaboration with Alice Labs has been easy, educational, and incredibly supportive. We engaged them to improve our processes and create more efficiency in the team, and the result truly exceeded expectations. Through their guidance, we've gained better structure, faster workflows, and more time for what actually creates results."
Frida
Partner Manager
Bruce Studios
"Fast, professional, and wonderful people. Find out for yourself <3"
Johannes Hansen
Founder
Johannes Hansen AB
AI agents automate the entire claims lifecycle: intake (extracting data from photos, documents, and forms), validation (cross-referencing policy terms and coverage limits), fraud scoring (pattern analysis across historical claims), and payout calculation. Simple claims (e.g., windshield replacement) can be processed end-to-end in minutes. Complex claims are triaged and routed to human adjusters with AI-prepared summaries.
No — and it shouldn't. AI augments underwriters by automating data collection, running risk models across hundreds of variables, and surfacing insights that would take hours of manual analysis. The underwriter makes the final decision, but with 10x more data and context, in a fraction of the time.
AI fraud detection analyzes behavioral patterns, claim histories, network connections (organized fraud rings), and anomaly signals that rule-based systems miss. Typical results: 30-50% more fraud detected, with 40-60% fewer false positives compared to rule-based approaches.
We implement AI across all insurance lines: property & casualty (P&C), life insurance, health insurance, commercial insurance, and reinsurance. Our solutions are adapted to the specific data structures, regulations, and workflows of each line.
AI agents provide 24/7 self-service for policy inquiries, claims filing, and status updates through natural language interfaces. They personalize communications, proactively alert policyholders about coverage gaps, and reduce response times from days to seconds.
Yes. Our implementations include model risk management frameworks, explainability reports, audit trails, and documentation that satisfy Solvency II pillar 2 (governance) and pillar 3 (disclosure) requirements. We work with your compliance team to ensure regulatory alignment.
AI enhances traditional actuarial models by incorporating alternative data sources (IoT, telematics, satellite imagery), identifying non-linear risk factors, and enabling real-time pricing adjustments. This is especially valuable for emerging risk categories where historical data is limited.
Health insurance AI runs within your private infrastructure. We implement data minimization, anonymization, and access controls that meet GDPR, HIPAA (for US operations), and local health data regulations. No patient data leaves your security perimeter.
Typical ROI metrics: 40-60% faster claims processing, 30-50% reduction in fraud losses, 20-30% improvement in underwriting accuracy, 50-70% reduction in manual data entry. Most insurers see positive ROI within the first quarter of deployment.
A focused pilot (one use case, e.g., claims triage) can be production-ready in 30-60 days. Full-scale deployment across claims, underwriting, and fraud detection typically takes 90-120 days. We follow an iterative approach: pilot → validate → scale.
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