Jedify raises $24M to give enterprise AI agents the business context they lack

Jedify Inc., an enterprise AI context startup, announced a $24 million Series A funding round to advance its platform, which builds a dynamic 'context graph' by linking a company’s operational data, documents, and workflows. The technology, called Semantic Fusion, creates a semantic model that updates in real-time to align AI agents with business-specific definitions, permissions, and workflows—addressing issues like hallucinations or irrelevant data processing. The company argues that enterprises relying on AI vendors for both models and data face misaligned incentives, leading to potential lock-in. Jedify’s model-agnostic approach avoids this by providing an independent layer that integrates with existing systems. It claims each interaction refines the context graph, making it a proprietary asset that grows over time. Jedify’s platform connects structured data from warehouses, CRM, and financial systems with unstructured sources like Slack threads and meeting recordings. Co-founder and CEO Assaf Henkin stated that enterprises need deep business understanding for AI workflows to function at scale, and Jedify’s solution transforms fragmented data into actionable insights. The funding round was led by Norwest, with strategic investments from Snowflake Ventures and participation from S Capital VC, Cerca Partners, and Oceans Ventures. Jedify previously raised $8.5 million in seed funding last year, bringing total funding to over $33 million. The new capital will support product development, hiring, and market expansion, including integration with Snowflake’s Cortex AI tools. Jedify’s technology is patent-pending and designed to work across AI models, giving enterprises flexibility while maintaining governance control. Norwest partner Assaf Harel emphasized the platform’s ability to autonomously fuse data into a smarter context graph, reducing vendor dependency and aligning with enterprise infrastructure needs.