The Knowledge system in Push.ai processes unstructured data through a pipeline that transforms raw content into a repository of context built around the structured model of your business.

Knowledge is currently only available on the Enterprise Plan.

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Artifacts

Artifacts are one of the foundational elements of the knowledge system, representing a piece of unstructured content, like a document, meeting, or Slack channel. Learn more about artifacts and their categories in our Artifacts documentation.

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Chunks

Chunks are the atomic building blocks of knowledge processing. We use artifact-specific chunking techniques to break down artifacts into meaningful segments while preserving their original context and structure. This approach enables:

  • Semantic Search: Breaking content into appropriately sized chunks allows for more precise and relevant search results
  • Context Preservation: Each chunk maintains its relationship to the original artifact and its position within the larger document
  • Citation Support: The chunking process preserves metadata and structural information needed for accurate citations

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Vector Embeddings and Inference

Once content is chunked, we use vector embeddings to transform text into numerical representations that capture semantic meaning. This enables:

  • Semantic Search: Finding relevant content based on meaning rather than just keywords
  • Context Mapping: Automatically connecting unstructured content to relevant business objects
  • Pattern Recognition: Identifying relationships and patterns across different pieces of content

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Business Graph Integration

The processed knowledge is then integrated with your Business Graph™ through:

  • Automatic Tagging: Content is automatically tagged with relevant business objects
  • Context Enrichment: Unstructured insights are used to enhance the context of structured data
  • Relationship Mapping: New relationships between business objects are discovered and mapped