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Warehouse Integrations

Warehouse integrations provide a powerful way to process and analyze unstructured data stored in your data warehouse:

  • Native Source Support: Process data from various sources (Slack, Notion, etc.) directly from your warehouse
  • Source-Specific Processing: Each source type (e.g., Slack messages, Notion pages) has its own optimized processing pipeline
  • Metadata Preservation: Maintain source-specific metadata and context throughout the processing pipeline
  • dbt Package Support: Leverage dbt packages to transform and prepare unstructured data for processing

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API Integrations

API integrations enable real-time processing of unstructured data from various sources:

  • Direct Source Connections: Connect to sources like Slack, Notion, and other platforms via their APIs
  • Real-time Processing: Process and analyze content as it’s created or updated
  • Source-Specific Chunking: Apply optimized chunking strategies based on the source type
  • Metadata Enrichment: Automatically enrich content with source-specific metadata

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File Uploads

File uploads provide a flexible way to process individual documents and content:

  • Direct Processing: Upload and process individual files or batches of files
  • Document Intelligence: Extract insights from various document types (PDFs, Word docs, etc.)

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Artifact-Specific Processing

Push.ai applies artifact-specific processing and chunking techniques:

  • Message Processing: Process chat messages with channel-level artifact grouping
  • Document Processing: Handle documents as single artifacts with recursive LLM-based chunking
  • Source-Agnostic Analysis: Apply consistent analysis techniques across different sources
  • Context and Metadata Preservation: Maintain relationships and metadata across artifacts and source context