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Context Data
Overview :
Context Data is a data processing and transformation platform designed for generative AI applications. It empowers AI teams to build data infrastructure, freeing them to focus on developing AI logic. It offers features such as:
- Building AI applications without setting up infrastructure
- Transforming data across multiple sources for comprehensive data integration
- Connecting to multiple models seamlessly, simplifying the data embedding process
- Supporting the loading of data into all major vector databases
- Providing querying functionality for private vector data
- Configuring scheduled pipelines to ensure data timeliness
- Gaining immediate responses through Query Studio
- Offering APIs and Python SDKs for building advanced applications and configurations. Context Data emphasizes data privacy control, avoiding uploading data to external models like OpenAI, thus simplifying the pressure and complexity of building an AI-ready data platform.
Target Users :
Designed for AI teams building and maintaining data infrastructure, Context Data streamlines data processing, allowing teams to focus on developing AI logic, improving efficiency, and ensuring data security and privacy.
Use Cases
An AI team utilizes Context Data to build its data infrastructure and focus on developing AI models.
A company uses Context Data to migrate data from Salesforce to MySQL, transforming and querying it.
Developers leverage Context Data's APIs and SDKs to create customized AI applications.
Features
Build AI applications without setting up infrastructure
Transform data across multiple data sources for comprehensive data integration
Connect to multiple models with one click, simplifying the data embedding process
Support loading data into all major vector databases
Provide querying functionality for private vector data
Configure scheduled pipelines to ensure data timeliness
Get instant responses through Query Studio
Leverage APIs and SDKs to build advanced applications and configurations
How to Use
Visit the Context Data website and register an account
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Connect to multiple external data sources, including embedded models and vector databases
Perform data transformation and integration from different sources through the platform
Use popular models to convert data into vector embeddings
Load the final data into supported vector databases
Configure pipelines to run on a schedule, ensuring data updates
Query data and obtain immediate responses using Query Studio
Build more advanced applications and configurations using APIs and SDKs
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