Unstructured
Research Team Data
Published
Data preparation layer for GenAI and RAG
Company profile
Overview
GenAI data platform that transforms complex, unstructured and multimodal data into clean, structured, AI-ready inputs for RAG, search, analytics, and LLM applications.
Processes 64+ file types with connectors, partitioning, VLM parsing, chunking, enrichment, embedding, and workflow/API endpoints to prepare enterprise data for RAG and GenAI pipelines.
At a glance
Key facts
- HQ location
- San Francisco, CA, USA
- Founded
- 2020
- Employee range
- 51-200
- Funding stage
- Series B
- Company type
- PrivatePrivate / open-source commercial
- Last updated
- Pricing model
- Licensing Open SourceSubscriptionUsage BasedOpen-source plus API/SaaS usage and enterprise plans
Business context
Financials
- Revenue estimate
- $7.7M ARR estimate (Latka, Jan 2025); company revenue not officially disclosed
- Valuation estimate
- ~$230M reported/estimated Series B valuation
- Investments
- $65M total; $40M Series B announced Mar 2024
Market context
Relationships
- Target customers
- Enterprise AI teams, developers, data teams, companies building RAG and knowledge applications
- Key competitors
- LlamaIndex, LangChain, Upstage, Haystack/deepset, Pinecone, Weaviate, Databricks
- Known customers
- Not publicly disclosed
Source context
Classification (raw research text)
- Core focus
- AI data ingestion and preprocessing
- Core industry
- AI Data Infrastructure
- Core category
- RAG data preparation platform
Shown verbatim from the research spreadsheet — deriving structured industry tags from this text is a future phase.
Market taxonomy
Segments, Industries & Certifications
Segments
AI WorkflowsAI Developer ToolsKnowledge & RAGDocument AIAI Governance & RiskChatbotsAnalytics & BI