DOCS-1113 Create ai accelerator ga documentation section

advocacy_docs/edb-postgres-ai/ai-accelerator/index.mdx

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+---
+title: "EDB Postgres AI - AI Accelerator"
+navTitle: "AI Accelerator"
+directoryDefaults:
+  product: "EDB Postgres AI"
+  iconName: BrainCircuit
+indexCards: simple
+description: "All about the EDB Postgres AI - AI Accelerator suite of tools including Pipelines and PGvector."
+navigation:
+- overview
+- pipelines
+redirects:
+- /edb-postgres-ai/ai-ml/
+---
+
+

advocacy_docs/edb-postgres-ai/ai-accelerator/overview.mdx

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+---
+title: "EDB Postgres AI - AI Accelerator - Overview"
+navTitle: "Overview"
+description: "Overview of the EDB Postgres AI AI Accelerator suite of tools including EDB PGvector and Pipelines."
+---
+
+## What is the AI Accelerator?
+
+AI Accelerator simplifies AI data management by combining vector search from open source PGvector with Pipelines, an extension for AI data pipeline automation. It handles vector embedding operations for structured and unstructured data, simplifying similarity searches and natural language querying, and streamlines development of AI-powered applications by providing retrieval of AI-ready data in a familiar Postgres environment.
+
+## Features
+
+### Vector Toolkit
+
+The EDB Pipelines extension enables automated vector embedding, storage, and retrieval workflows, and it comes preloaded with PGvector for seamless management of vector data in Postgres. This enables developers to build complex GenAI functionality using SQL commands in the familiar Postgres environment — with just 5 lines of code instead of 130+.
+
+### Swappable Configurations
+
+Easily switch between models, integrate multiple data modalities, and select from a variety of storage locations — in the cloud or on prem — enabling tailored performance and efficient data management that adapts to any need across your business.
+
+### Automated Pipelines
+
+Simplify data processing with Automated Pipelines for fetching data from Postgres or object storage, generating vector embeddings as new data is ingested, and triggering updates to embeddings when source data changes — meaning always-up-to-date data for query and retrieval without tedious maintenance.
+
+### GenAI Query Engine
+
+Leverage semantic search across text and images that’s 4.22X faster[^1] than purpose-built vector databases and an Intelligent Retriever that abstracts away the complexities of vector similarity calculations — transforming your Postgres database into a powerful GenAI search engine across multiple storage locations.
+
+[^1]: [Why we replaced Pinecone with PGVector](https://www.confident-ai.com/blog/why-we-replaced-pinecone-with-pgvector) Confident AI blog post.
+
+## Use cases
+
+* **Sovereign AI**: Your controlled, adaptable AI Platform. Secure, flexible, and cost-effective where your data lives.
+* **Virtual Expert**: Natural language AI agents (e.g. chatbots, copilots) to improve workforce and customer outcomes.
+* **Cognitive AI**: Intelligent search, analysis, and recommendation across diverse data types.
+

advocacy_docs/edb-postgres-ai/ai-accelerator/pgvector/index.mdx

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+---
+title: "AI Accelerator - PGvector"
+navTitle: "PGvector"
+description: "PGvector is a Postgres extension that provides vector data types and functions to store and manipulate vector data."
+deepToC: true
+---
+
+## What is PGvector
+
+PGvector is an extension for Postgres that enables efficient storage and similarity search of high-dimensional vector data, commonly used for machine learning models, recommendation systems, and natural language processing applications.
+
+### Part of the EDB Postgres AI platform
+
+EDB Postgres AI with PGvector delivers a flexible solution for enterprise AI, integrating seamlessly with existing Postgres environments. It outperforms standalone vector databases with 4.22X faster queries and eliminates data silos via integrations with 18X cost-efficient object storage. This unified platform accelerates AI deployment, simplifies management, and ensures up to 99.999% availability, enabling businesses to innovate rapidly and future-proof their data infrastructure without disrupting current operations.
+
+### Native Vector Data Type Support
+
+PGvector on EDB Postgres AI enables storage of AI/ML model embeddings as first-class data types, allowing efficient indexing and querying of large volumes of AI data stored in object storage, seamlessly integrated with traditional relational data.
+
+### Advanced 4.22X Vector Query
+
+Extends standard SQL with vector-specific operators and functions, enabling complex queries that combine vector operations, relational data, and full SQL capabilities, going far beyond simple similarity searches to support sophisticated AI-driven applications.
+
+### High-performance Indexing 
+
+With real-time indexing, storage, and querying of AI data, PGvector enables efficient vector similarity search on embeddings from various LLMs, while leveraging Postgres transactionality for consistent handling of mixed workloads.
+
+### Integrated Vector Data Platform
+
+PGvector unifies vector database capabilities with EDB Postgres AI's mature enterprise features, ensuring high availability, robust backup/recovery, strong security, and ACID data integrity, all within a single vendor solution for comprehensive data management and AI workloads.
+
+## Installation
+
+The extension is included with AI Accelerator's Pipelines and installed automatically when Pipelines is installed.
+
+## Further information
+
+For more information on the PGvector extension, see the [PGvector repository](https://github.com/pgvector/pgvector).

advocacy_docs/edb-postgres-ai/ai-accelerator/pipelines/gettingstarted/index.mdx

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+---
+title: "Getting Started with Pipelines"
+navTitle: "Getting Started"
+description: "How to get started with AI Accelerator Pipelines."
+---
+
+## Where to Start
+
+The best place to start is with the [Pipelines Overview](/edb-postgres-ai/ai-accelerator/pipelines/overview) to get an understanding of what Pipelines is and how it works.
+
+## Installation
+
+Pipelines is included with the EDB Postgres AI - AI Accelerator suite of tools. To install Pipelines, follow the instructions in the [AI Accelerator Installation Guide](/edb-postgres-ai/ai-accelerator/pipelines/installing).
+
+## Using Pipelines
+
+Once you have Pipelines installed, you can start using it to work with your AI data.
+
+###TODO
+

advocacy_docs/edb-postgres-ai/ai-accelerator/pipelines/index.mdx

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+---
+title: "AI Accelerator - Pipelines"
+navTitle: "Pipelines"
+indexCards: simple
+iconName: BrainCircuit
+description: "Installing and using AI Accelerator Pipelines with the aidb and PGFS extensions."
+navigation:
+- "#Introducing"
+- overview
+- installing
+- gettingstarted
+- "#Components"
+- models
+- retrievers
+- pgfs
+- "#Resources"
+- reference
+- rel_notes
+- licenses
+---
+
+As part of the EDB Postgres AI platform, Pipelines abstracts away the complexity of working with AI data. It transforms Postgres into a powerful platform for AI data management, as it combines vector search from PGvector with automation for complex AI workflows.

advocacy_docs/edb-postgres-ai/ai-accelerator/pipelines/installing/complete.mdx

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+---
+title: "Completing and verifying the extension installation"
+navTitle: "Completing the installation"
+description: "Completing and verifying the installation of the AI Database and File System extensions."
+---
+
+### Installing the AI Database extension
+
+The AI Database extension is an extension that provides a set of functions to run AI/ML models in the database. The extension is installed using the `CREATE EXTENSION` command.
+
+```sql
+ebd=# CREATE EXTENSION aidb CASCADE;
+NOTICE:  installing required extension "vector"
+CREATE EXTENSION
+edb=#
+```
+
+### Installing the File System extension
+
+The File System extension is an extension that provides a set of functions to interact with the file system from within the database. The extension is installed using the `CREATE EXTENSION` command.
+
+```sql
+edb=# create extension pgfs;
+CREATE EXTENSION
+```
+
+### Validating the installation
+
+You can check the extensions have been installed by running the `\dx` command in `psql`.
+
+```sql
+edb=# \dx
+__OUTPUT__
+                                     List of installed extensions
+       Name       | Version |   Schema   |                        Description
+------------------+---------+------------+------------------------------------------------------------
+ aidb             | 1.0.1   | aidb       | aidb: makes it easy to build AI applications with postgres
+ pgfs             | 1.0.2   | pgfs       | pgfs: enables access to filesystem-like storage locations
+ vector           | 0.7.4   | public     | vector data type and ivfflat and hnsw access methods
+```
+
+Typically, there will be other extensions listed in this view. The `aidb`, `pgfs`, and `vector` extensions should be listed.

advocacy_docs/edb-postgres-ai/ai-accelerator/pipelines/installing/index.mdx

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+---
+title: "Installing AI Accelerator Pipelines"
+navTitle: "Installing"
+description: "How to install AI Accelerator Pipelines."
+navigation:
+- packages
+- complete
+---
+
+Pipelines is delivered as a set of extensions. Depending on how you are deploying Pipelines, these extensions may be installed by your deployment platform (such as EDB Cloud Service) or if you deploy your own Postgres server, you will need to install them manually.
+
+- [Manually installing pipelines packages](packages)
+
+Once the packages are installed, you can [complete the installation](complete) by activating the extensions within Postgres.
+

advocacy_docs/edb-postgres-ai/ai-accelerator/pipelines/installing/packages.mdx

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+---
+title: "AI Accelerator - Pipelines"
+navTitle: "Installing packages"
+description: "How to install the aidb and PGFS extensions from packages."
+prevNext: true
+---
+
+## Installing the extension packages
+
+There are three extension packages that are required to use the AI Accelerator Pipelines:
+
+- `aidb` - The AI Database extension
+- `pgfs` - The PGFS (Postgres File System) extension
+- `vector` - The PGvector extension
+
+### Prerequisite
+
+This guide assumes you have a PostgreSQL server running. You can install AI Accelerator Pipelines on a Community PostgreSQL server, an EDB Postgres Advanced Server, or an EDB Postgres Extended server. Consult the installation guides for those products if you need help setting up a server. When you install the server, make a note of the package name used as it will be needed to install the AI Accelerator Pipelines packages.
+
+- For Community PostgreSQL, the package name is `postgresql-<version>`.
+- For EDB Postgres Advanced Server, the package name is `edb-as<version>` followed by `-server`.
+- For EDB Postgres Extended, the package name is `edb-postgresextended-<version>` followed by `-server`.
+
+Once you have established the package name, you can install the server using the package manager for your operating system.
+
+### Installing the packages
+
+Once the server is running, there will be a number of packages that need to be installed. The packages are available in the EDB repository, and can be installed using the appropriate package manager for your operating system. You will need to use either:
+
+- `apt` for Debian/Ubuntu based systems with .deb packages
+- `dnf` for Red Hat based systems with .rpm packages
+
+Depending on your operating system. The packages are:
+
+#### For Community PostgreSQL
+
+- `edb-pg<version>-aidb` - The AI Database extension
+- `edb-pg<version>-pgfs` - The File System extension
+
+and for the Vector extension either:
+
+- rpm-based systems: `edb-pg<version>-pgvector0`
+- deb-based systems: `edb-pg<version>-pgvector-0`
+
+#### For EDB Postgres Advanced Server
+
+- `edb-as<version>-aidb` - The AI Database extension
+- `edb-as<version>-pgfs` - The File System extension
+
+and for the Vector extension either:
+
+- rpm-based systems: `edb-as<version>-pgvector0`
+- deb-based systems: `edb-as<version>-pgvector-0`
+
+#### For EDB Postgres Extended
+
+- `edb-pgextended-<version>-aidb` - The AI Database extension
+- `edb-pgextended-<version>-pgfs` - The File System extension
+
+and for the Vector extension either:
+
+- rpm-based systems: `edb-postgresextended<version>-pgvector0`
+- deb-based systems: `edb-postgresextended<version>-pgvector-0`
+
+
+!!! Note Example
+Installing the packages on Ubuntu 22.04, with EDB Postgres Advanced Server 16 would look like this:
+
+```shell
+sudo apt-get install edb-as16-aidb edb-as16-pgfs edb-as16-pgvector-0
+```
+
+With the packages installed, you can now connect to the database and [complete the installation the extensions in Postgres](complete).
+
+!!!