Unlock the power of unstructured data with LLMs

Airbyte moves your unstructured and semi-structured data and makes it accessible to any vector database & popular LLM frameworks.

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Utilize LLMs to extract relevant  information & insights from your data

Build RAG pipelines, employ ML techniques for data classification, or fine tune your language models, all leveraging your data.

Empower GenAI workflows by moving data into AI-enabled data warehouses

Leverage the native vector support offered by Snowflake Cortex and Bigquery’s Vertex AI to power your Gen AI applications.

Use Airbyte’s Snowflake Cortex destination to directly store vector data in Snowflake!

Get started with Snowflake Cortex

Build Retrieval based LLM apps on top of synced data

Add a retrieval based conversational interface to raw or transformed data loaded using Airbyte.

Use your favorite LLM frameworks like LangChain or LlamaIndex. Build AI co-pilots, agents, workflows and more.

Build a chat app using LangChain

Understand your data via LLM-powered actionable insights

Use Airbyte to combine data from diverse sources, improving the accuracy of your NLP tasks.

Provide actionable insights into your data by building ML applications involving sentiment analysis, clustering and classification.

Check our MindsDB tutorial

Create training datasets & fine tune ML models specific to your use case

Train models using domain-specific or proprietary data from your company and customers.

Models drift over time. Airbyte ensures you have the latest data needed to train and maintain model performance over time.

Learn how to fine tune your LLM

Get your data LLM ready!

Flexible data movement that works seamlessly with your LLM tooling and existing workflows.

Consolidate your unstructured and structured data in one place

Leverage Airbyte’s large catalog of source connectors to move raw data into your preferred storage destination.You have full control on how you transform your raw data. Use our intuitive UI to set up data connections, or deploy our open-source connectors in Kubernetes.

Get started with Airbyte

Pull your data directly into a vector database destination

Automatic chunking and indexing options lets you transform your raw data and store it in 8 different vector db destinations. Generate embedding using our pre-built set of LLM providers or provide your own. Compatible with OpenAI, Cohere, Anthropic and other popular LLM providers.

Browse vector database destinations

Streamline data transformation using our Python library

PyAirbyte packages Airbyte’s catalog of sources into a python library allowing you to load data from Airbyte sources into a local cache. Load data from various sources and merge or transform it in code before storing it to your preferred database.

Learn more about PyAirbyte

Deploy your pipelines your way

Self-hosted or cloud-hosted, connectors for your own usage or embedded in your own product.

Airbyte Cloud

We’ll host for you, and scale with you as you grow
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Airbyte Self-Managed

Pay for Support or enterprise features while staying on-prem.
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Locate the text data source connectors you need

Centralize that unstructured and semi-structured data in any of the vector databases we support, so you can calculate text embeddings and structure that data.

Check our tutorials

20 minutes

How to Create an LLM Application with ChromaDB & Airbyte

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Learn how to build a robust Large Language Model application using ChromaDB for vector storage and Airbyte for data integration, simplifying your AI development workflow.