The Enterprise AI Suite Engineered for Trust
About Kagen
- AWS Technology Partner / Gartner 2025 Cool AI Vendors
- Observed stalled AI pilots → built agentic OS
- Proud Microsoft Gold and Google Cloud Partner
Kagen delivers AI-first enterprise products that automate workflows, enhance compliance, unlock insights, and drive secure, scalable operational efficiency.
See how Kagen’s multi-agent architecture transforms raw data into intelligent action.

From Data to Decision: The Kagen Workflow
From data ingestion to decision: Kagen’s agents work in concert. Integration Agents bring in data, Processing Agents refine it, Ontology Agents contextualize it, and Application Agents act – all under the watchful governance of the Super Layer.
Security & Governance Built-In
Role-based access and audit logs ensure enterprise compliance.
Scalable Orchestration
Seamlessly manage and scale thousands of agents across workloads.
Interoperability
Connects easily with your existing data, APIs, and AI tools
Observability & Monitoring
Real-time dashboards and alerts for full visibility into agent performance.
Multi-Cloud Deployment
Run anywhere-AWS, Azure, or on-prem-without reconfiguration.
Unlike patchwork AI tools, Kagen delivers a unified operating system for enterprise AI.





Kagen.ai is committed to the highest standards of security, privacy, and quality. Our platform and processes are undergoing rigorous certification to give you peace of mind.

Kagen’s paper on a reinforcement learning nutrition agent has been accepted at IEEE CASCON 2025, spotlighting our innovation in AI for healthcare. Co-authored by our Chief AI Officer, the study introduces Diextra, an AI coach that analyzes meal photos and adapts dietary advice using reinforcement learning. In early trials, Diextra achieved over 90% nutrient estimation accuracy, underscoring Kagen’s agentic approach to improving diabetes management.
At CASCON 2025, researchers unveiled a pioneering project, Reinforcement Learning-Driven Nutrition Coaching that merges computer vision and reinforcement learning to personalize diabetes self-management. Developed by Dr. Priyamvada Tripathi, Dr. Nikhil Gupta, and Dr. Kanav Kahol, the system adapts meal recommendations in real time using user feedback and health data, outperforming traditional rule-based plans. Powered by TensorFlow, FastAPI, and AWS, this adaptive AI coach boosts engagement and glycemic control, marking a major step toward intelligent, precision-driven nutrition and chronic care.


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