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Update product section of docs
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SilasMarvin committed Jul 9, 2024
commit 0cf476b4d716eb3836160b36c418bd22c735f31a
16 changes: 8 additions & 8 deletions pgml-cms/docs/SUMMARY.md
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* [Installation](open-source/pgcat/installation.md)
* [Configuration](open-source/pgcat/configuration.md)

## Product

* [PostgresML Cloud](product/postgresml-cloud/README.md)
* [Serverless](product/postgresml-cloud/serverless.md)
* [Dedicated](product/postgresml-cloud/dedicated.md)
* [Enterprise](product/postgresml-cloud/plans.md)

## Guides

* [Embeddings](guides/embeddings/README.md)
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* [Unified RAG](guides/unified-rag.md)
* [OpenSourceAI](guides/opensourceai.md)
* [Natural Language Processing](guides/natural-language-processing.md)

## Product

* [Cloud database](product/cloud-database/README.md)
* [Serverless](product/cloud-database/serverless.md)
* [Dedicated](product/cloud-database/dedicated.md)
* [Enterprise](product/cloud-database/plans.md)
* [Vector database](product/vector-database.md)

## Resources

* [Architecture](resources/architecture/README.md)
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# PostgresML Cloud

PostgresML Cloud is the best place to perform in-database ML/AI.

It’s a fully managed version of our popular open-source extension that combines the robustness of PostgreSQL with specialized AI capabilities and hardware (GPUs). PostgresML Cloud provides the infrastructure and compute engine for users to deliver state-of-the-art AI-driven applications – without the headache of managing a database or GPUs.

You’ll have access to a powerful suite of production-ready ML/AI capabilities from day one, while PostgresML Cloud takes care of all the performance, scalability, security, and reliability requirements typical of database and hardware management. An added bonus is that the PostgresML Cloud approach to GPU management is inherently more cost-effective than purchasing them yourself.

## PostgresML Cloud Plans

PostgresML Cloud offers three configurations to suit various project needs and organizational sizes, from small teams just starting with AI integration to large enterprises requiring advanced features and dedicated support.

PostgresML Cloud is available on Amazon Web Services (AWS), Google Cloud Platform (GCP) and Microsoft Azure Cloud, world-wide.

[Learn more about plans and pricing](/pricing)

### Serverless

Quickly and easily create a PostgresML engine that can scale from very little capacity to gigabytes of GPU cache and terabytes of disk storage. Ideal for teams that want to start small and grow as their usage of PostgresML increases.

[Learn more about serverless](serverless)

### Dedicated

Dedicated plans provide a large assortment of hardware, including CPU and GPU configurations, near-bottomless storage capacity and horizontal scaling into millions of queries per second. Ideal for larger startups and enterprises that have established PostgresML as their AI database of choice.

[Learn more about dedicated](dedicated)

### Enterprise

Enterprise plans are ideal large companies that have special compliance needs and deployment configurations; with options for cloud-prem (VPC), on-prem, ACL’s and more.

[Learn more about enterprise](enterprise)
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