| Description |
| Summary |
GenAI data platform that transforms complex, unstructured and multimodal data into clean, structured, AI-ready inputs for RAG, search, analytics, and LLM applications.
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| Description |
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.
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| Positioning |
Data preparation layer for GenAI and RAG
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| Key facts |
| HQ location |
San Francisco, CA, USA
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| Founded |
2020
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| Employee range |
51-200
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| Funding stage |
Series B
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| Company type |
Private
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| Pricing model |
licensing open source, subscription, usage based
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| Last updated |
Jun 21, 2026
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| Financials |
| Revenue estimate |
$7.7M ARR estimate (Latka, Jan 2025); company revenue not officially disclosed
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| Valuation estimate |
~$230M reported/estimated Series B valuation
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| Investments |
$65M total; $40M Series B announced Mar 2024
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| Relationships |
| Target customers |
Enterprise AI teams, developers, data teams, companies building RAG and knowledge applications
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| Key competitors |
LlamaIndex, LangChain, Upstage, Haystack/deepset, Pinecone, Weaviate, Databricks
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| Known customers |
Not publicly disclosed
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| Segments & Industries |
| Segments |
AI Workflows, AI Developer Tools, Knowledge & RAG, Document AI, AI Governance & Risk, Chatbots, Analytics & BI
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