We started Superlinked almost 4 years ago to help developers build real-time personalized software and last year we closed our first 6-figure customer contract. Over the years, instead of investing in customer-specific ranking models, we found a way to use open-source and proprietary models to turn complex product listings, content, user behavior and other types of data into vector embeddings. To enable software engineers to query these multi-modal vectors effectively, we have built a mechanism to define and prioritise for relevance, freshness, popularity and other objectives simultaneously. Finally, we incorporated backfills and batch query evaluation into our product to address common data engineering challenges in managing systems into production. Together, we call these systems “the vector computer”.
Today, we are open-sourcing the interactive components of Superlinked with a goal to help the industry run vector-powered systems in production and combine unstructured and structured data for accurate RAG, Search, RecSys and Analytics. Here is how Superlinked fits into the enterprise data stack:
Starburst powers analytics and ETL workflows for 100s of enterprises, moving and aggregating petabytes of data across a complex data landscape. Our clients rely on this data to answer questions and generate insights, increasingly within Gen AI-powered workflows. Starburst is collaborating with Superlinked to extract and transform complex data into vector embeddings, enabling enterprises to take full advantage of their first party data to differentiate their Generative AI offerings
Harrison JohnsonVP of Technology Partnerships