Files
supabase/apps/docs/content/guides/ai.mdx
Taryn King 65c6929414 chore(docs): update docs to use postgres over postgresql language (#44881)
## I have read the
[CONTRIBUTING.md](https://github.com/supabase/supabase/blob/master/CONTRIBUTING.md)
file.

YES

## What kind of change does this PR introduce?

Updates verbiage throughout docs to use postgres over postgresql.


<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->

## Summary by CodeRabbit

* **Documentation**
* Updated terminology throughout documentation, guides, and resources
for consistent product naming across all user-facing materials,
including page titles, descriptions, and reference documentation.

<!-- end of auto-generated comment: release notes by coderabbit.ai -->
2026-04-15 09:49:45 +00:00

97 lines
3.6 KiB
Plaintext

---
id: 'ai'
title: 'AI & Vectors'
description: 'The best vector database is the database you already have.'
subtitle: 'The best vector database is the database you already have.'
hideToc: true
---
Supabase provides an open source toolkit for developing AI applications using Postgres and pgvector. Use the Supabase client libraries to store, index, and query your vector embeddings at scale.
The toolkit includes:
- A [vector store](/docs/guides/ai/vector-columns) and embeddings support using Postgres and pgvector.
- A [Python client](/docs/guides/ai/vecs-python-client) for managing unstructured embeddings.
- An [embedding generation](/docs/guides/ai/quickstarts/generate-text-embeddings) process using open source models directly in Edge Functions.
- [Database migrations](/docs/guides/ai/examples/headless-vector-search#prepare-your-database) for managing structured embeddings.
- Integrations with all popular AI providers, such as [OpenAI](/docs/guides/ai/examples/openai), [Hugging Face](/docs/guides/ai/hugging-face), [LangChain](/docs/guides/ai/langchain), and more.
## Search
You can use Supabase to build different types of search features for your app, including:
- [Semantic search](/docs/guides/ai/semantic-search): search by meaning rather than exact keywords
- [Keyword search](/docs/guides/ai/keyword-search): search by words or phrases
- [Hybrid search](/docs/guides/ai/hybrid-search): combine semantic search with keyword search
## Examples
Check out all of the AI [templates and examples](https://github.com/supabase/supabase/tree/master/examples/ai) in our GitHub repository.
{/* <!-- vale off --> */}
<div className="grid md:grid-cols-12 gap-4 not-prose">
{aiExamples.map((x) => (
<div className="col-span-4" key={x.href}>
<Link href={x.href} passHref>
<GlassPanel icon={'/docs/img/icons/github-icon'} hasLightIcon={true} title={x.name}>
{x.description}
</GlassPanel>
</Link>
</div>
))}
</div>
{/* <!-- vale on --> */}
## Integrations
{/* <!-- vale off --> */}
<div className="grid md:grid-cols-12 gap-4 not-prose">
{aiIntegrations.map((x) => (
<div className="col-span-4" key={x.href}>
<Link href={x.href} passHref>
<GlassPanel title={x.name}>{x.description}</GlassPanel>
</Link>
</div>
))}
</div>
{/* <!-- vale on --> */}
## Case studies
{/* <!-- vale off --> */}
<div className="grid md:grid-cols-12 gap-4 not-prose">
{[
{
name: 'Berri AI Boosts Productivity by Migrating from AWS RDS to Supabase with pgvector',
description:
'Learn how Berri AI overcame challenges with self-hosting their vector database on AWS RDS and successfully migrated to Supabase.',
href: 'https://supabase.com/customers/berriai',
},
{
name: 'Firecrawl switches from Pinecone to Supabase for Postgres vector embeddings',
description:
'How Firecrawl boosts efficiency and accuracy of chat powered search for documentation using Supabase with pgvector',
href: 'https://supabase.com/customers/firecrawl',
},
{
name: 'Markprompt: GDPR-Compliant AI Chatbots for Docs and Websites',
description:
"AI-powered chatbot platform, Markprompt, empowers developers to deliver efficient and GDPR-compliant prompt experiences on top of their content, by leveraging Supabase's secure and privacy-focused database and authentication solutions",
href: 'https://supabase.com/customers/markprompt',
},
].map((x) => (
<div className="col-span-4" key={x.href}>
<Link href={x.href} passHref>
<GlassPanel title={x.name}>{x.description}</GlassPanel>
</Link>
</div>
))}
</div>
{/* <!-- vale on --> */}