Context Data is an enterprise data platform that simplifies the process of building data infrastructure for Generative AI applications. The platform was created by a team that has years of experience working with enterprise companies to build extensive data solutions and warehouses. As the team noticed the explosion of Generative AI applications, they saw a huge gap in the market for data pre-processing and transformations built specifically for vector databases. Context Data was built to allow 'real' enterprise companies to use the data and ETL processes they're already familiar with to build vector data stores for their Generative AI applications and use cases. Context Data aims to serve as a centralized data processing platform and pipeline that companies of all sizes can use to move and transform their data without having to spin up infrastructure or write massive amounts of ETL code and logic. The platform provides no-code connectivity to multiple data sources, the ability to transform and combine data across those sources, generate vector embeddings, and load the final data to any major vector database - all in a matter of minutes instead of weeks.
Context Data provides a plug-and-play data infrastructure that requires no setup or installation.
Connect to a variety of data sources, including databases, SaaS applications, and APIs, without writing any code.
Use SQL or Python to transform and enrich your data, creating a fully contextual dataset for your Generative AI applications.
Convert your data to vector embeddings using popular models like OpenAI, Cohere, and Anthropic, without setting up any infrastructure.
Load your transformed and embedded data to any of the major vector database providers without writing any code.
Query your private vector data using the Context Data platform, without the need to manage any infrastructure.