Infrastructure in Research & Data
10 companies using infrastructure technology in the research & data sector. AI/ML infrastructure, compute networks, and tooling
Directory
Companies by Funding
Snowflake
AI-enhanced data platform for finance
Together AI
Open-source AI inference
Ocean Protocol (OCEAN/FET)
Decentralized data marketplace
Render (RENDER)
Decentralized GPU rendering network
Vana
User-owned data network for AI
Grass
Distributed data scraping network
Cambrian Network
Onchain/offchain data for automated financial decision-making; API for agents
Akash Network
Decentralized cloud for AI computing
Related
Other AI Technologies in Research & Data
Related
Infrastructure in Other Segments
Frequently Asked Questions
How is Infrastructure used in research & data?
AI/ML infrastructure, compute networks, and tooling In the research & data sector, Infrastructure is applied by 10 companies tracked by AIFI Map, with $1.3B in combined funding. Leading companies include Snowflake (AI-enhanced data platform for finance); Together AI (Open-source AI inference); Ocean Protocol (OCEAN/FET) (Decentralized data marketplace).
Which research & data companies use Infrastructure?
The AIFI directory tracks 10 research & data companies using Infrastructure, with a combined $1.3B in funding. Snowflake, Together AI, Ocean Protocol (OCEAN/FET), Render (RENDER), Vana, and 3 more. (Source: AIFI Map directory.)
What is the most funded Infrastructure research & data company?
Snowflake is the most funded company using Infrastructure in research & data, with $621M raised. AI-enhanced data platform for finance Followed by Together AI ($534M).
How does Infrastructure compare to other AI technologies in research & data?
In the Research & Data segment, Infrastructure ranks #3 out of 8 AI technologies by adoption, with 10 companies and $1.3B in combined funding. The most widely adopted technologies in research & data are Data Platform (29 companies, $19.1B funded); LLM / NLP (19 companies, $105.5B funded); Infrastructure (10 companies, $1.3B funded). While Infrastructure focuses on ai/ml infrastructure, compute networks, and tooling, alternative approaches include Data Platform, which data aggregation and enrichment platforms with minimal ml, and LLM / NLP, which large language models for nlp, chat, document understanding, and text generation.