Jedify raises $24M to build context graphs for enterprise AI agents

AI agents promise turnkey enterprise automation, but they often fail without deep business context. Jedify, a New York-based startup, addresses this by creating a 'context graph' — a multi-dimensional layer that captures relationships between data, people, permissions, and workflows. The platform connects via APIs to structured sources (databases, data warehouses, BI tools) and unstructured ones (Slack channels, meeting recordings, reports). This graph updates in real time, allowing agents to narrow their focus to task-relevant information. Co-founder and CEO Assaf Henkin explains that unlike semantic layers or knowledge graphs, Jedify’s approach is model-agnostic and inherits permissions from identity systems, file systems, and databases — ensuring interns don’t see CFO projections.

Jedify has raised $24 million in Series A funding co-led by Norwest, with participation from S Capital VC, Cerca Partners, and Oceans Ventures. Data giant Snowflake also invested strategically and is integrating Jedify into its Cortex AI, Semantic Views, and CoWork products. The company targets mid-market and large enterprises with mature data stacks and counts The Weather Company among 10–20 early customers. Henkin argues that while big cloud platforms try to build similar capabilities, much of a company’s data resides outside a single provider, making Jedify complementary. The platform also offers observability and governance tools to monitor agent behavior.