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Tensorlake is designed to be the ingestion and processing layer for your AI stack. We provide seamless integrations with leading orchestration frameworks, vector databases, and data platforms to help you build end-to-end workflows.

Orchestration Frameworks

Build powerful agents and RAG pipelines by combining Tensorlake’s document understanding with your preferred framework.

LangChain

Use Tensorlake loaders and tools directly within your LangChain chains and agents.

OpenAI Agents SDK

Power your OpenAI agents with structured data extraction and document processing tools.

Vector Databases

Index your parsed documents efficiently for Retrieval Augmented Generation (RAG).

Qdrant

Upsert structured points and embeddings directly into Qdrant collections.

Chroma

Store and retrieve document chunks with rich metadata in ChromaDB.

Data Platforms

Turn unstructured documents into analytical tables for SQL queries and business intelligence.

Databricks

Load extracted data into Databricks Delta Tables for large-scale analytics.

MotherDuck

Query your parsed documents using SQL with DuckDB in the cloud.

Advanced Processing

Enhance your pipelines with specialized processing tools.

Chonkie

Semantic chunking that respects the structure of your Tensorlake-parsed documents.