vector-embeddings
(5)
Nomic AI
Nomic AI is a New York-based artificial intelligence company building tools to make large, unstructured datasets and AI models understandable and usable by everyone. It is best known for Atlas, a browser-based platform for visualizing and interacting with massive datasets; the open-source Nomic Embed family of text, code, and multimodal embedding models; and GPT4All, an ecosystem for running large language models privately on everyday hardware. Since 2025 the company has focused its platform on the architecture, engineering, and construction (AEC) sector, applying its embedding and retrieval technology to drawing review, code compliance, and document-heavy construction workflows.
Vectara
Vectara is a Palo Alto-based enterprise AI company building a trusted, end-to-end platform for retrieval-augmented generation (RAG) and AI agents. Founded in 2022 by former Google AI researchers, it lets companies embed grounded, citation-backed GenAI - conversational assistants, semantic search, and agents - into their products while actively detecting and correcting hallucinations at runtime. Its stack includes the Boomerang embedding model, the RAG-tuned Mockingbird LLM, the open-source Hughes Hallucination Evaluation Model (HHEM), and a Guardian Agent layer, positioning Vectara as a leader in factual, secure, compliance-ready enterprise AI.
Superlinked, Inc.
Superlinked is a San Francisco-based infrastructure company building the 'vector computer' - a compute and data engineering framework that turns complex enterprise data into vector embeddings for Search, RAG, Recommendations and Analytics. It now also ships an open-source Inference Engine that lets agent teams self-host every model their agents call, claiming roughly 50x cost savings vs hosted per-token APIs.
LlamaIndex
LlamaIndex is a San Francisco company building the data framework and cloud platform that lets enterprises turn messy unstructured documents into knowledge agents powered by large language models. Its open-source library is one of the most-used scaffolds for retrieval-augmented generation, and its hosted product, LlamaCloud, packages parsing, extraction, and indexing for production teams.
Daniel Svonava
Daniel Svonava is the Co-Founder and CEO of Superlinked, an ML infrastructure company building self-hosted inference infrastructure for vector search and document processing. A Slovak-born engineer and entrepreneur based in San Francisco, he spent six years as an ML Tech Lead at YouTube building ad performance systems powering over $10B in annual ad revenue before co-founding Superlinked in 2021. Superlinked raised a $9.5M seed round led by Index Ventures in March 2024, and the company is on a mission to make vector-based retrieval accessible and production-ready for enterprises.