Jedify secures $24 million Series A to build context layers for enterprise AI agents
Led by Norwest with strategic backing from Snowflake, the funding round brings Jedify’s total capital raised to approximately $33 million as it seeks to standardise how AI agents navigate complex corporate data environments.
Jedify, a New York-based startup, has raised $24 million in a Series A funding round to develop a platform that constructs "context graphs" for enterprise artificial intelligence agents. The round was led by Norwest, with participation from S Capital VC, Cerca Partners, and Oceans Ventures. Strategic investor Snowflake also participated in the round, reflecting a growing alliance between data infrastructure providers and specialised AI middleware developers.
The capital will be deployed for product development, hiring, and go-to-market activities, bringing the company’s total funding to approximately $33 million. Jedify’s core proposition addresses a persistent friction point in enterprise AI adoption: the difficulty of integrating autonomous agents into fragmented corporate data stacks without extensive custom engineering.
The platform connects to diverse enterprise knowledge sources via APIs, including databases, data warehouses, SaaS applications, business intelligence tools, and unstructured sources such as Slack channels and meeting recordings. By mapping relationships between entities, permissions, domain knowledge, and workflows, Jedify aims to provide AI agents with a structured understanding of business context that allows them to narrow their focus to task-relevant information rather than searching across entire data repositories.
Co-founder and chief executive Assaf Henkin argues that Jedify’s approach differs from traditional semantic layers or metadata catalogs by being model-agnostic and multi-dimensional. The system inherits permissions from identity systems, file systems, and databases, enforcing row-, column-, and table-level access rules to ensure agents operate within defined security boundaries. This governance layer is critical for preventing data leakage, such as ensuring junior staff do not gain access to sensitive financial projections.
Early adopters include Kiteworks, which has integrated Snowflake, Tableau, and Notion to build agentic tools for sales and account teams, as well as The Weather Company. Snowflake is currently integrating Jedify’s technology with its own AI products, including Cortex AI, Semantic Views, and CoWork. The startup is targeting mid-market and large enterprise customers with mature data stacks, seeing particular interest from the gaming, industrials, and consumer packaged goods sectors.
