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InsOps is building the AI Small Language Model (SLM) for insurance. Generic AI was not built for insurance. It lacks domain context, struggles with insurance-specific rules and relationships, and often requires sensitive data like PII & PHI data to leave controlled environments, creating accuracy and compliance risks. InsOps’ insurance-trained AI SLM solves these problems by understanding insurance data, workflows, and regulations, while operating within the insurer’s environment. This makes our AI SLM platform and the tools it powers ideal for the following use cases: Data privacy protection: As insurance data moves across systems and workflows, the risk of exposing PII and PHI increases. InsOps transforms insurance data into privacy-safe data by design by automatically detecting and protecting PII and PHI as data moves. The data remains usable for testing, analytics, and operations, while significantly reducing breach impact and re-identification risk. This approach supports compliance with GDPR, GLBA, and HIPAA across operational workflows. Workflow automation: InsOps removes the manual effort required to keep insurance workflows running. Data no longer needs to be repeatedly moved, checked, or corrected as it flows through policy, claims, billing, and partner processes. Routine handoffs are handled automatically, reducing delays and rework, and allowing teams to focus on serving customers and running the business. Data migration and modernization: InsOps allows Insurers to migrate decades of legacy data across core systems such as Guidewire, Duck Creek, Origami, and legacy platforms using one AI-powered platform, rather than separate tools for each system in under 6 months.

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Navajeevan Rajaiah is the Founder and CEO of InsOps.

6 people are employed at InsOps.

InsOps is based in Warrenville, Illinois.

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