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Introduction:
PostgresML is an MLOps platform built as a PostgreSQL extension, enabling the creation of machine learning models directly within your database. It provides GPU-accelerated Postgres databases for AI applications, supporting vector embeddings, real-time inference, and more. By consolidating vector databases, embedding models, and LLMs into a single system, PostgresML streamlines the AI development stack.
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PostgresML Product Information
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 utilized via SQL or through SDKs for JavaScript and Python. Users can execute tasks such as text generation, embedding creation, and vector database operations directly within PostgreSQL. The platform supports a variety of open-source models and provides the capability to fine-tune LLMs using your own data.
PostgresML's Core Features
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Build and deploy ML models directly within PostgreSQL
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GPU-powered Postgres databases for AI applications
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Vector embedding and real-time output generation
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Integration with open-source models (Mistral, Llama, etc.)
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Support for SQL and SDKs in JS and Python
PostgresML Use Cases
#1
Retrieval Augmented Generation (RAG)
#2
Search
#3
Chatbot development
#4
Text generation
#5
Embeddings
#6
Vector database operations
#7
Supervised learning
FAQ from PostgresML
What is PostgresML? +
PostgresML is an MLOps platform implemented as a PostgreSQL extension that enables you to build and deploy machine learning models directly within your database.
What tasks can I perform with PostgresML? +
You can perform a variety 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 a range of open-source models, such as Mistral and Llama, and provides the ability 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, which reduces the complexity of managing multiple microservices.
PostgresML Pricing
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