Datavid grounds AI outputs in real enterprise data using semantics, knowledge graphs, and FAIR principles. This ensures results are explainable, reproducible, and compliant, unlike generic LLMs that rely only on public training data.

We help enterprises build contextual search systems, regulatory or clinical copilots, explainable AI pipelines, and agentic workflows. Our approach combines structured data, semantic enrichment, and retrieval-augmented generation to deliver trusted outcomes.

With accelerators like Datavid Rover, organizations can launch AI pilots in 6–8 weeks. Our lean, expert teams ensure fast delivery of governed, scalable AI platforms that integrate with your existing data stack.