Quality, lineage on every knowledge asset
Agents are only as good as the data behind them, yet most enterprise knowledge is scattered, unstructured, and ungoverned. Data and Knowledge Studio is the unified environment for data and knowledge engineering that standardizes, governs, and packages enterprise data into trusted, context-rich, AI-ready assets every agent can consume.
Generic RAG breaks on messy enterprise data. Data and Knowledge Studio turns documents, databases, and APIs into governed retrieval assets through RAG, GraphRAG, and ontology-driven pipelines, with profiling, quality, classification, and lineage wired in so every asset is trusted, traceable, and reusable.
RAG, GraphRAG, and OKF pipelines in one place, choose the right grounding pattern per use case.
Profiling, quality, classification, and lineage are wired into every pipeline, not added afterward.
Every output is standardized and context-rich, ready for agent grounding, search, and NLQ.
Data and Knowledge Studio builds the retrieval pipelines (RAG, GraphRAG, OKF) and manages the underlying data. Semantic Fabric supplies the ontologies and knowledge graphs they ground against. They work together. Pipelines feed the fabric, the fabric gives them meaning.
It depends on the use case: RAG for document-heavy Q&A, GraphRAG when relationships between entities matter, and OKF when answers must align to enterprise ontologies. The studio supports all three in one place.
No. Data collection and extraction connects to your existing documents, databases and APIs, and pipelines run over that estate, with classification and lineage tracked throughout.
Data profiling and quality management validate sources before use, data classification flags sensitivity, and lineage tags trace every asset back to its origin for full auditability.
We appreciate your interest. We will get in touch shortly.