PostgresML
MLOps platform as a PostgreSQL extension for building ML models inside the database.
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- MLOps platform as a PostgreSQL extension for building ML models inside the database
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- MLOps platform as a PostgreSQL extension for building ML models inside the database
Overview
PostgresML is a complete MLOps platform implemented as a PostgreSQL extension. It allows users to build fast, simple, and powerful machine learning models directly within their database. It offers GPU-powered Postgres databases for building AI applications, enabling tasks like vector embedding, real-time output generation, and more. PostgresML simplifies the AI stack by integrating various components like vector databases, embedding models, and LLMs into a single system.
Access & connections
Where you can use PostgresML, and what it plugs into.
Platforms
Integrations
Capabilities
What this tool accepts, produces, and is strongest at.
Highlights
- Build and deploy ML models directly within PostgreSQL
- GPU-powered Postgres databases for AI applications
- Vector embedding and real-time output generation
- Integration with open-source models (Mistral, Llama, etc.)
- Support for SQL and SDKs in JS and Python
FAQ 6
What is PostgresML?
PostgresML is a complete MLOps platform implemented as a PostgreSQL extension. It allows users to build fast, simple, and powerful machine learning models directly within their database. It offers GPU-powered Postgres databases for building AI applications, enabling tasks like vector embedding, real-time output generation, and more. PostgresML simplifies the AI stack by integrating various components like vector databases, embedding models, and LLMs into a single system.
How to use PostgresML?
PostgresML can be used through SQL or SDKs in JS and Python. Users can perform tasks like text generation, embedding creation, and vector database operations directly within PostgreSQL. The platform supports various open-source models and allows for fine-tuning LLMs on user data.
What is PostgresML?
PostgresML is a complete MLOps platform implemented as a PostgreSQL extension, allowing you to build and deploy machine learning models directly within your database.
What tasks can I perform with PostgresML?
You can perform a range of AI and machine learning tasks, including text generation, embedding creation, vector database operations, supervised learning, RAG, search, and chatbot development.
What models does PostgresML support?
PostgresML supports various open-source models, including Mistral, Llama, and others. It also allows you to fine-tune LLMs on your own data.
How does PostgresML simplify the AI stack?
PostgresML integrates components like vector databases, embedding models, and LLMs into a single system, reducing the complexity of managing multiple microservices.
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PostgresML