DataWeave Debuts LLM-Native Data Fabric and Closes $50M Series B

AI · 6 min read

The data fabric ingests structured and unstructured sources, creates canonical knowledge graphs and emits context windows tailored to downstream model prompts. DataWeave emphasizes lineage, verifiability and refresh semantics so teams can control what the model sees during inference.

With the funding, DataWeave will expand connectors for scientific publishers, regulatory feeds and internal data lakes, and build governance UIs that let compliance teams set content policies at ingestion. Customers in pharma and legal sectors highlighted the fabric’s audit trails as critical for regulated LLM deployment.

DataWeave is offering an enterprise edition with on-prem and hybrid options to meet strict security requirements. The company says adoption spikes when product teams combine the fabric with embedding-based retrieval and evaluation pipelines to reduce hallucination risk.