Trusted answers when it matters

Traditional search leaves out valuable results or requires sifting through responses. Knowledge graph-powered smart search is sound and complete.

Exploding volumes of information make it harder to find the right information. Whether you’re building an internal knowledge base or a user-facing app, Stardog ensures you’ll find the best results.

Complete, correct, and explainable results

Having trouble determining the appropriate scope of your project? Our experts can advise on data governance, metadata management, data lineage and pedigree, and more to help you assess your priorities. We’ll help you take that first critical step in developing a data-centric strategy that aligns to business goals.

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the SpringerMaterials research platform

Search across structures and sources

Unlock all relevant data sources to power search across SQL, NoSQL and full-text documents. Stardog’s virtual graph capability ensures that live data can be accessed, reducing data redundancy and ensuring the most up-to-date data is accessed. With data unified across sources, users save time finding the answers they need.

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Bosch’s Power Tool search app

The best backend for intelligent applications

Use Stardog to organize the data for your chatbot or recommendation engine. AI depends on providing intelligent answers, and knowledge graphs enable this by mapping the myriad associations between concepts. The result: user intent is more easily captured, providing better results.

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National Bank of Canada’s smart hub

  • Quote

    My Smart Hub allows employees to spend less time searching, discovering, getting answers, and automating repetitive tasks”

    Senior Director, Digital Transformation, National Bank of Canada



Stardog easily incorporates new data sources, allowing for easy iterative development of search applications


Where some AIs cannot provide explanations for results, Stardog offers proofs for all query results for easy interpretation


BITES translates full-text documents into searchable data, capturing concepts and their relationships

Built-in ML

Use built in predictive analytics and similarity search to develop models to improve recommendations in search results