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Superlinked
Superlinked helps AI engineers build high-performance search, recommendation, and RAG applications by turning structured and unstructured data into vector embeddings. It provides a Python framework…
Superlinked
Superlinked helps AI engineers build high-performance search, recommendation, and RAG applications by turning structured and unstructured data into vector embeddings. It provides a Python framework…
TL;DR
What they do: Platform and open-source framework for self-hosted inference, vector embeddings, search, recommendations, and RAG workflows
Product highlight: SIE (Superlinked Inference Engine) for self-hosted inference and document processing
Founded: 2018
Headcount: 33 employees
Funding: Seed rounds; total reported funding ~10.56M USD; last round Mar 18, 2024
Company Overview
Problem Domain
Production semantic search, recommendation systems, and retrieval-augmented generation using vector embeddings and document processing.
Founded
2018
Industry
Data Infrastructure and Analytics
Tech Stack
Funding Track Record
Investor Signal
“Has multiple early-stage investors including venture firms and angels (e.g., Index Ventures, MMC Ventures, Bob van Luijt, others)”
Founders
What we do
Join the Team
Startup jobs. A lot of them.
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