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Enterprise AI platforms · San Francisco, United States
Built on the open-source project that made large-scale data processing practical, Databricks has repositioned itself as the platform enterprises use to actually build AI on top of their own data - a less visible but arguably more durable business than a consumer chatbot.
Databricks was founded in San Francisco in 2013 by Ion Stoica, Andy Konwinski, Reynold Xin and several other creators of Apache Spark, the open-source data-processing engine that began as a UC Berkeley research project. The company built a commercial platform - the "lakehouse" - around Spark that combines data warehousing and data-lake storage, and has expanded aggressively into generative AI tooling: model training, fine-tuning, RAG pipelines and its own MosaicML-derived open models, sold to enterprises that need to build AI applications on top of their own governed data.
Databricks has raised capital at an unusually fast pace through 2026 even for the sector, with its reported valuation roughly tripling within a year.
Databricks Data Intelligence Platform
Unified data lakehouse and AI development platform.
Mosaic AI
Model training, fine-tuning and serving tools, built on technology from Databricks' 2023 acquisition of MosaicML.
AI safety-focused lab behind the Claude model family, founded by former OpenAI researchers.
Toronto-based enterprise large language model company, built by former Google Brain and DeepMind researchers.
The open-source AI platform and model-hosting hub that much of the industry builds on - agreed to be acquired by Nvidia in September 2026.
