Iris.ai
AI knowledge foundation for regulated enterprises — turning complex data into AI you can trust
Enterprise·Technical·API available
Key strengths
Agentic RAG-as-a-Service for regulated enterprisesUnified ingestion of complex, heterogeneous enterprise dataReal-time monitoring and CI/CD pipelines for AI agentsOver 330M documents securely ingested at scale35%+ savings on LLM usage costs through optimized evaluation
Enterprise pricing
Oslo, Norway
Founded 2015
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Use Cases — Technical Perspective
Iris.ai is suited for enterprise AI deployments where the following technical requirements are present:
- Closed-corpus question answering: Teams need an LLM-powered assistant that is strictly grounded in internal documentation — engineering specs, regulatory filings, research reports — rather than open-domain knowledge.
- Regulated industry compliance: The step-level measurement of the answer pipeline supports audit trails required in life sciences, energy, and other regulated sectors.
- High-accuracy retrieval in manufacturing and telecom: Operational environments where a model misreading a technical document could cause downstream errors benefit from the platform's controlled retrieval scope.
- Enterprise knowledge management: Organizations looking to make expert knowledge locked in internal systems queryable without exposing that data to external model training or shared infrastructure.
These use cases are unified by the need for accuracy guarantees and full observability over model behavior.
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