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Cloud & Infrastructure

Build more with Pinecone.

Vector database for building AI applications with semantic search and recommendations. Shape those capabilities into a system that fits your team.

Build concepts, not preinstalled apps. Provider plans, permissions, and API availability apply.

The possibilities

What could you build?

01

Knowledge search app

Retrieve relevant approved content for a focused internal search experience.

02

Product discovery assistant

Use semantic retrieval to suggest items from your own indexed catalog.

Start with the knowledge search app.

Keep the first version small enough to test with the people who will use it.

  1. 01
    Pinecone
  2. 02
    Knowledge search app
  3. 03
    Reviewed next action
  1. 01

    Choose the first job

    Use the first idea as your brief: Retrieve relevant approved content for a focused internal search experience. Name the person responsible and the information they need to act.

  2. 02

    Confirm access before connecting

    Keep namespaces and filters aligned with access rules. Track source IDs and remove vectors when source content is deleted.

  3. 03

    Shape the app with Scout

    Use the starter prompt below. Ask Scout to propose the records, source field mapping, views, and access rules. Preview sample data before connecting Pinecone; keep source IDs so records stay traceable.

  4. 04

    Pilot, then expand

    Test with a small approved dataset and a least-privileged user. Check missing records, revoked access, repeated events, and failed requests. Enable live writes or messages only after the responsible owner approves the workflow.

Start with this prompt

Paste into Scout, then adapt it to your team. Do not paste credentials or private customer data.

Create this app with Pinecone: Knowledge search app. Retrieve relevant approved content for a focused internal search experience. Start with sample data and a small, approved set of records. Before connecting live data: Keep namespaces and filters aligned with access rules. Track source IDs and remove vectors when source content is deleted. Propose the data model, access rules, and source-to-app field mapping before implementation. Add source links, a last-updated time, and clear empty and connection-error states. Keep credentials out of client code. Require human approval for external messages, source changes, or money movement. Test duplicate events, revoked access, and recovery before publishing.

Take it further

Make it work your way.

Start with Scout, or map the first build with our team.