Unstructured, a Sacramento, CA-based provider of large language models (LLMs) data preprocessing solutions, raised $25M in Seed and Series A funding.
The Series A was led by Madrona with participation from the seed lead, Bain Capital Ventures, and joined by M12 Ventures, Mango Capital, MongoDB Ventures, and Shield Capital. Angel investors Harrison Chase of LangChain, Bob van Luijt of Weaviate, and Josh Lefkowitz of Flashpoint also participated. As part of the financing, Madrona Managing Director Karan Mehandru and Bain Capital Ventures Partner Enrique Salem joined the board of directors.
The company intends to use the funds to expand operations and its business reach.
Led by Brian Raymond, Founder and CEO, Unstructured is a provider of LLM data preprocessing solutions, empowering organizations to transform their internal unstructured data into formats compatible with large language models. The company has also launched an API that transforms 20+ natural language file types from raw to LLM-ready and enterprise-grade data connectors, including for Azure Blob, Microsoft OneDrive, Amazon S3, Google Cloud Storage, Google Drive, Dropbox, Elasticsearch, and more. By automating the extraction, cleaning, and staging of natural language data, it enables enterprises to leverage data for increased productivity and innovation.
Unstructured offers three ways to get started: a rich open-source Python library, open-source containers, and a cloud-hosted API.
The company has developed its technology in partnership with the open-source community and commercial enterprises, as well as select U.S. Government defense and intelligence organizations. It has been awarded a Phase I and two Phase II Small Business Innovation and Research contracts by the U.S. Air Force and U.S. Space Force. Additionally, U.S. Special Operations Command (SOCOM) established a Cooperative Research and Development Agreement with Unstructured and has served as a key design partner since the company’s infancy. This past winter, Unstructured partnered with SOCOM to help deploy the first use of an LLM on a stand-alone system and in conjunction with mission-relevant data.
FinSMEs
19/07/2023