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Welcome to Qontext

Qontext is your unified context layer. It transforms scattered company data into AI-ready context. By connecting to the tools your company already uses, Qontext organizes information into Context Vaults: living, structured context graphs that your AI workflows can query directly. Instead of reinventing knowledge management, you simply connect, ingest, and retrieve, and your AI always operates with accurate, up-to-date context.

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How Qontext Works

  • Ingest your data: Connect your existing sources like HubSpot, Notion, or Google Drive, or ingest unstructured data (text, JSON, markdown, websites) directly via the API.
  • Automatic structuring: Qontext continuously organizes information into Context Vaults, connecting entities and maintaining relationships as your data changes.
  • Retrieve your context: Query Qontext from any AI workflow, chat interface, or API call to get the precise, connected context your model needs, automatically ranked for relevance.

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Why Qontext Matters

Traditional RAG (retrieval-augmented generation) systems stop at keyword or vector similarity. Qontext goes beyond RAG. It captures the relationships between entities and adapts as your data evolves.
  • Relationship-aware context: Retrieves connected entities, not just isolated snippets.
  • Adaptive company memory: Updates continuously as facts change. No manual re-ingestion needed.
  • Relevance-first retrieval: Re-ranks results by contextual importance, not just rigid similarity metrics.
  • Unified access layer: Use the same structured context across all tools, APIs, and workflows.
In short, Qontext turns your company’s scattered data into a living, contextual memory for your AI systems.