
Data & intelligence infrastructure for Generative AI applications
Context Data is a low-code enterprise data platform that automates the deployment of data pipelines and ETL infrastructure for Generative AI applications. It enables companies to connect to internal and external data sources, run SQL-based transformations, generate vector embeddings, and load data into managed vector databases — reducing deployment time from weeks to under 10 minutes. The platform is SOC 2 Type I and II compliant and supports flexible deployment including on-premises and private cloud environments.
Connect to internal and external data systems and build end-to-end data pipelines without writing ETL code, reducing deployment from weeks to under 10 minutes.
Native integrations to databases, file storage systems, and external CRMs, enabling unified data ingestion from across the enterprise.
Create complex data transformation logic using SQL to join data from multiple sources before writing to a target database or vector store.
Provision and manage vector databases and indexes backed by Pinecone in a matter of minutes, without managing the underlying infrastructure.
Automatically generate vector embeddings from your structured and unstructured data sources as part of the pipeline workflow.
Automatically generate data ontologies that map all source data, embedding models, vector databases, and their connections for full lineage visibility.
Teams building RAG chatbots or search tools use Context Data to automate the data ingestion, transformation, and vector embedding pipeline without custom engineering.
Businesses wanting an internal ChatGPT-like assistant over their own documents and CRMs can deploy a private AI chatbot using Context Data's platform.
Small and mid-size businesses without dedicated data engineering teams use the low-code interface to build production-grade AI data pipelines.
Enterprises with existing data warehouses use Context Data to apply SQL transformations to produce vector-ready datasets for AI and search applications.
Deploy within Context Data's SOC 2 compliant cloud, on a private server, or within your own firewall for maximum data privacy and control.
Query your vector databases using natural language, enabling non-technical users to interact directly with AI-indexed company data.
Schedule recurring pipeline runs to keep vector stores up to date with the latest data from connected sources automatically.

Enterprise automation platform with 1,200+ connectors for seamless integration