New York-based startup Jedify has raised $24 million in Series A funding to expand a platform designed to provide AI agents with a deeper understanding of how businesses operate.
The round was led by Norwest and included participation from existing investors S Capital VC and Cerca Partners, as well as new investor Oceans Ventures. Snowflake joined as a strategic investor.
The funding brings Jedify’s total capital raised to about $33 million.
Building a “context graph”
Jedify connects to enterprise systems through APIs and creates what it calls a context graph, which AI agents can use to access business-specific information.
The platform integrates with:
- Databases.
- Data warehouses and lakes.
- SaaS applications.
- Business intelligence tools.
- Documentation.
- Code repositories.
- Slack channels.
- Meeting recordings.
According to the company, the goal is to help AI agents understand:
- Relationships between data and entities.
- Permissions and access rights.
- Internal workflows.
- Company terminology.
- Operational assumptions.
That allows agents to focus on information relevant to a specific task rather than searching across an entire organization.
Example use case
Chief executive and co-founder Assaf Henkin pointed to compliance software company Kiteworks as an example.
Kiteworks connected:
- Snowflake.
- Tableau.
- Notion.
- Internal playbooks.
- Documents.
- Screenshots.
The company then built AI tools to support customer-facing workflows.
“They wanted to arm their sellers and account teams with a sophisticated app — you can think of it as both like a dashboard application and a real-time conversational application,” Henkin told TechCrunch.
“When they go into a customer conversation, Jedify builds for them, on the fly, everything they need to know.”
Real-time updates
Henkin said the context graph differs from existing semantic layers, metadata catalogs, and knowledge graphs because it captures relationships across multiple dimensions.
These include:
- Data.
- People.
- Customers.
- Permissions.
- Business entities.
The platform is model-agnostic and updates continuously as connected systems change.
“When you want to enable an agentic solution to really be autonomous, to drive decisions across CRM data, Zendesk tickets, maybe telemetry data that’s coming in real time, that’s when a context graph is much better in terms of capabilities versus a semantic layer,” Henkin said.
Handling permissions
Jedify said it inherits access controls from:
- Identity systems.
- File systems.
- SaaS tools.
- Databases.
The platform supports:
- Row-level permissions.
- Column-level permissions.
- Table-level access rules.
Customers can also create additional restrictions governing what AI agents are allowed to access.
The company provides monitoring and governance tools intended to ensure agents operate within approved boundaries.
Early customers
Jedify is focusing on mid-sized and large enterprises with complex data environments.
Henkin said the company currently has between 10 and 20 early customers.
Among them is The Weather Company.
Interest has also come from sectors including:
- Gaming.
- Industrials.
- Consumer packaged goods.
Partnership with Snowflake
Snowflake is integrating Jedify’s technology with products including:
- Cortex AI.
- Semantic Views.
- CoWork.
Henkin argued that large cloud data providers cannot capture all of a company’s knowledge because information is often spread across multiple systems.
“[The large data companies] will tell you, ‘Oh yeah, just bring everything.’ But in reality, companies have multiple databases, and warehouses, and data solutions,” he said.
He added that much of an organization’s institutional knowledge resides outside any single platform.
Betting on context
As AI models become more capable and increasingly interchangeable, Jedify believes proprietary business context will become a critical advantage.
The company plans to use the new funding for:
- Product development.
- Hiring.
- Go-to-market efforts.
TL;DR
Jedify has raised $24 million to help AI agents understand company-specific data, workflows, permissions, and terminology. The startup’s “context graph” platform is already being used by early enterprise customers and is being integrated with Snowflake’s AI products.
AI summary
- Jedify raised $24 million in a Series A round led by Norwest.
- The startup builds “context graphs” for enterprise AI agents.
- Snowflake invested and is integrating Jedify’s technology.
- Early customers include The Weather Company and Kiteworks.
- The company says business context could become a key AI advantage.
