Unstructured Raises $25 Million to Bring Order to the Chaos for Language Model Data
Madrona leads Series A for data transformation startup
There’s so much excitement around vector databases these days that the startup that makes it easier for companies to organize their data so they can plug it into vector databases just raised $25 million across its seed and Series A rounds.
Unstructured, a company founded by ex-CIA analyst Brian Raymond, is announcing today that it has raised a $20 million Series A round led by Madrona with participation from Bain Capital Ventures. M12 Ventures, Mango Capital, MongoDB Ventures, and Shield Capital also participated in the round as did angel investors Harrison Chase of LangChain, Bob van Luijt of Weaviate, and Josh Lefkowitz of Flashpoint.
Bain Capital Ventures led Unstructured’s $5 million seed round.
“How do you get your data to a vector database? That’s where we come in on the easy button,” Raymond said.
Vector databases store information in a way that makes it easier to quickly compare different types of information and find possible similarities. They’ve become a key vehicle for inputting information into large language models.
Raymond told me that Unstructured’s users mostly want to fine-tune foundation models off their proprietary data — not build their own foundation models from the ground up.