Enterprise artificial intelligence context startup Jedify Inc. today announced that it has raised $24 million in new funding to build what it calls context graphs that give AI agents the business knowledge they need to run in production.

Jedify sells software that automatically assembles a customer-specific “context graph” on top of a company’s existing data and knowledge systems. The platform links a company’s operational data, held in warehouses, customer relationship management and financial systems, with the unstructured material scattered around it: documents, playbooks, Slack threads and meeting recordings. Out of that, Jedify says, it builds a semantic model that keeps current on how the business defines its metrics, how its records relate and who is allowed to see what.

Enterprise AI deployments have struggled with exactly this gap. Large language models can produce fluent answers but cannot reliably determine which definition of revenue applies, which customer record is current or which operational assumptions matter unless that context is supplied at runtime. Without it, the company argues, agents either hallucinate or burn tokens processing irrelevant information.

“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 co-founder and Chief Executive Assaf Henkin. “Enterprise data is fragmented across systems, definitions, permissions and workflows. Jedify turns that fragmented knowledge into a live context graph that agents can use to produce accurate, cost-efficient, business-ready answers.”

Jedify positions itself as a model-agnostic layer that sits apart from the model providers. The company argues that enterprises handing their data to the same vendors selling them tokens face misaligned incentives, a reference to recent moves by OpenAI Group PBC, Anthropic PBC and Google LLC to offer customers forward-deployed engineers and professional services. Jedify says an independent context layer avoids that conflict and the single-vendor lock-in that clashes with most large organizations’ governance requirements.

The technology underpinning the platform, which Jedify calls Semantic Fusion, is patent-pending. The company says each interaction makes a customer’s context graph more accurate, turning it into a proprietary asset that compounds over time. Jedify is also working with Snowflake Inc. to integrate with its Cortex AI tools, including Semantic Views and Cortex Analyst.

The funding will go toward product development, go-to-market expansion and hiring.

Norwest led the Series A round, with a strategic investment from Snowflake Ventures and participation from existing backers S Capital VC and Cerca Partners alongside new investor Oceans Ventures. Assaf Harel, a partner at Norwest, will join Jedify’s board.

“Jedify is solving a foundational problem by autonomously fusing structured and unstructured data into a context graph that gets smarter with every interaction,” Harel said. “Its compounding value and model-agnostic approach give enterprises flexibility rather than lock-in, which is exactly the kind of durable infrastructure layer we look for.”

Jedify raised an $8.5 million seed round in September 2023 led by S Capital VC, bringing total funding to more than $33 million.

Photo: Jedify