Korr provides a cloud‑native core insurance platform that unifies claims processing, policy administration, billing, and product configuration into a single system of record.
Funding
$3.2M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Insurance carriers rely on legacy core systems that are inflexible, require extensive custom code, and impede rapid product launches and AI integration. Maintaining and extending these outdated platforms adds operational cost and slows response to market changes.
Solution
Korr offers a cloud‑native core insurance platform that consolidates claims processing, policy administration, billing, and product configuration into a single modern system of record. The platform is built on a scalable Amazon S3 data store and provides real‑time, unified data without synchronization lag, enabling immediate analytics and AI‑driven decision support. Business rules, rating logic, and workflow definitions are managed through a configuration‑first model that supports no‑code setup and optional JavaScript, Python, or YAML extensions for complex scenarios. Deployments can be completed in 3–6 months, with fully managed hosting or hybrid AWS options, allowing insurers to replace legacy stacks quickly while keeping their teams lean. By delivering a flexible, API‑ready foundation, Korr lets carriers launch new products faster, adapt to regulatory changes, and embed AI tools directly into their core processes.
Target Audience
Primary customers are property‑ and casualty insurers, life insurers, and managing general agents that need a modern, flexible core system to accelerate product development and improve operational efficiency.
Features
- Unified cloud‑native core covering claims, policy administration, billing, and product configuration on a single platform
- Configuration‑first approach with no‑code rule definition and support for JavaScript, Python, and YAML for advanced customizations
- Real‑time data warehouse as the system of record, eliminating sync jobs and enabling instant analytics and AI integration
- Scalable Amazon S3‑based storage architecture that simplifies migration from mainframe legacy systems
- Rapid implementation timeline (3–6 months) with fully managed service or hybrid deployment in customer‑owned AWS environments
- Built‑in AI enablement layer for automation, decision support, and generative AI‑assisted rule creation
- API and integration framework that fits into existing enterprise stacks without extensive re‑engineering