This company provides data processing and ETL solutions specifically designed for building and deploying Generative AI applications. Their Sapphire platform enables businesses to securely connect diverse data sources, transform the data, and implement private Retrieval-Augmented Generation (RAG) frameworks. This allows organizations to query internal documents, databases, and other assets using AI without custom coding, ensuring enterprise-grade privacy and security.
Funding
$120K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
AI teams often struggle with the complexities of building and managing data pipelines for generative AI applications, including setting up infrastructure, transforming data from various sources, and loading it into vector databases. This process can be time-consuming and divert resources away from core model development.
Solution
Context Data provides an enterprise data pipeline platform designed to streamline data transfer from diverse sources, such as MySQL and Salesforce, to any vector database. The platform automates data processing, transformation using SQL or Python, and scheduling, eliminating the need for manual infrastructure setup. Context Data also features an open-source ETL framework, enabling users to build semantic transformations by combining, joining, or aggregating data across multiple platforms. The platform automatically generates data catalog graphs, mapping source data, transformations, vector data, and associated lineages. By simplifying the data integration process, Context Data allows AI teams to focus on model development and deployment.
Target Audience
Context Data targets AI teams, financial institutions, healthcare providers, real estate agencies, and supply chain companies seeking to streamline data integration for generative AI applications.
Features
- No-code connectivity to multiple data sources, including MySQL and Salesforce
- Cross-platform ETL, enabling transformations across separate platforms
- Semantic transformations using SQL or Python for data aggregation and contextualization
- Automated generation of data catalog graphs for data lineage tracking
- Support for converting data to vector embeddings with popular models
- Compatibility with major vector database providers
- Automated data processing and scheduling for up-to-date data
- Role-based access control for controlled data privacy