Jedify raises $24 million Series A to build context layer for enterprise AI
The startup says fragmented business data is blocking deployment of agentic AI systems.
Israeli-founded startup Jedify has raised $24 million in Series A funding as investors double down on infrastructure designed to help artificial intelligence systems understand how businesses actually operate.
The round was led by Norwest, with a strategic investment from Snowflake Ventures and participation from existing backers S Capital VC and Cerca Partners, alongside new investor Oceans Ventures. Norwest partner Assaf Harel will join the company’s board.
The financing brings Jedify’s total funding to just over $33 million, following an $8.5 million Seed round in September 2023.
Jedify was founded in 2023 by Assaf Henkin (CEO), Adi Elimelech (CTO) and Erik Shani (CPO) and employs 35 people.
The company is positioning itself at the center of a growing concern in enterprise AI: while large language models have improved rapidly, most corporate deployments still struggle to move beyond prototypes because they lack reliable business context at runtime.
Jedify argues that this missing layer, what it calls a “context graph,” is the difference between AI systems that generate plausible answers and those that can reliably operate inside complex enterprise environments.
“In order for an agentic workflow to really work well for an enterprise at scale, it needs a very deep understanding of that business,” said Assaf Henkin, co-founder and CEO of Jedify. “Enterprise data is fragmented across systems, definitions, permissions, and workflows.”
Jedify’s platform is designed to address that fragmentation by building an autonomous, continuously updated semantic model across an organization’s data systems. It connects structured data from warehouses, CRMs, financial systems and BI tools with unstructured sources such as documents, Slack messages and meeting recordings.
The result, the company says, is a live “context graph” that captures business definitions, entity relationships, operational rules, and domain-specific terminology, allowing AI agents to operate with a more consistent understanding of how an organization functions.
Jedify positions itself as a model-agnostic infrastructure layer intended to sit between enterprise data systems and AI applications, allowing organizations to use different model providers without locking themselves into a single ecosystem.
