Pinecone Integration — Automate Pinecone with AI on Beauto

Long-term Memory for AI. The Pinecone vector database makes it easy to build high-performance vector search applications. Developer-friendly, fully managed, and easily scalable without infrastructure hassles.

Category: artificial intelligence, databases · 48 actions available

What you can automate with Pinecone

Beauto connects Pinecone with 900+ other apps so you can build AI-powered workflows in minutes. Trigger automations from Pinecone events, enrich Pinecone data with AI, or sync Pinecone with the rest of your stack — without writing code.

  • Sync Pinecone data with Gmail, Slack, Notion, HubSpot, Google Sheets, and more
  • Trigger AI agents on new Pinecone events and route the output anywhere
  • Schedule recurring Pinecone tasks — daily reports, cleanups, or bulk updates
  • Use natural language to describe the workflow; Beauto builds it for you

Pinecone actions Beauto supports

  • Cancel Bulk Import — Tool to cancel a bulk import operation in Pinecone. Use when you need to stop an ongoing import operation that is not yet finished.
  • Configure Index — Tool to configure an existing Pinecone index, including pod type, replicas, deletion protection, and tags. Use when you need to scale an index vertically or horizontally, enable/disable deletion protection, or update tag
  • Create Backup — Tool to create a backup of a Pinecone index for disaster recovery and version control. Use when you need to preserve the current state of an index including vectors, metadata, and configuration.
  • Create Index — Tool to create a Pinecone index with specified configuration. Use when you need to initialize a new vector database index for storing and querying embeddings.
  • Create Index with Embedding Model — Tool to create a Pinecone index with integrated embedding model for automatic vectorization. Use when you need to set up a new index that automatically converts text to vectors using a pre-configured embedding model.
  • Create Index from Backup — Tool to create an index from a backup. Use when you need to restore or duplicate index data from a previously saved backup.
  • Create Namespace — Tool to create a namespace within a serverless Pinecone index. Use when you need to organize vectors into isolated partitions.
  • Delete Index — Tool to permanently delete a Pinecone index. Use when you need to remove an index from your project. Note: Deletion protection and pending collections can prevent deletion.
  • Delete Namespace — Tool to permanently delete a namespace from a serverless index. Use when you need to remove an entire namespace and all its data. This operation is irreversible and only supported on serverless indexes.
  • Describe Backup — Tool to retrieve detailed information about a specific backup. Use when you need to check backup status, configuration, or metadata.
  • Describe Bulk Import — Tool to describe a specific bulk import operation in Pinecone. Use when you need to retrieve detailed information about an import's status, progress, timing, and any errors.
  • Describe Index Stats — Tool to get index statistics including vector count per namespace, dimensions, and fullness. Use when you need to understand the contents and status of an index.
  • Describe Restore Job — Tool to get detailed information about a specific restore job in Pinecone. Use when you need to check the status, progress, or metadata of a restore operation.
  • Generate Embeddings — Tool to generate vector embeddings for input text using Pinecone's hosted embedding models. Use when you need to convert text into vector representations for semantic search or similarity matching.
  • Get Model Information — Tool to retrieve detailed information about a specific model hosted by Pinecone. Use when you need to understand model capabilities for embedding and reranking operations.
  • List Bulk Imports — Tool to list all recent and ongoing bulk import operations in Pinecone. Use when you need to monitor or track the status of data import jobs. Supports pagination with a default limit of 100 imports per page.
  • List Collections — Tool to list all collections in a Pinecone project (pod-based indexes only). Use when you need to view available collections.
  • List Index Backups — Tool to list all backups for a specific Pinecone index. Use when you need to view available backups for an index. Supports pagination via limit and paginationToken parameters.
  • List Indexes — Tool to list all indexes in a Pinecone project. Use when you need to retrieve all indexes with their configurations and status information.
  • List Available Models — Tool to list all available embedding and reranking models hosted by Pinecone. Use when you need to discover available models or filter by model type (embed/rerank) or vector type (dense/sparse).
  • List Namespaces — Tool to list all namespaces in a serverless Pinecone index. Use when you need to discover available namespaces for data organization. Returns up to 100 namespaces by default with pagination support.
  • List Project Backups — Tool to list all backups for indexes in a Pinecone project. Use when you need to retrieve backup information across all project indexes. Supports pagination with limit and paginationToken parameters.
  • List Restore Jobs — Tool to list all restore jobs for a project with pagination support. Use when you need to view the status of restore operations or track restore progress.
  • List Vectors — Tool to list vector IDs in a Pinecone serverless index. Use when you need to browse or retrieve vector identifiers from a namespace. Supports filtering by prefix and pagination for large result sets.
  • Query Vectors — Tool to perform semantic search within a Pinecone index using a query vector. Retrieves IDs and similarity scores of the most similar items, ordered from most to least similar. Either vector or id parameter must be provi
  • Rerank Documents — Tool to rerank documents by semantic relevance to a query. Use when you need to order retrieved documents by their semantic relevance to a user's search query using Pinecone's hosted reranking models.
  • Search Records in Namespace — Tool to search records within a Pinecone namespace using text, vector, or ID query. Use when you need to find similar records based on embeddings or record IDs. Results can optionally be reranked for relevance.
  • Start Bulk Import — Tool to start an asynchronous bulk import of vectors from object storage (S3, GCS, or Azure Blob Storage) into a Pinecone index. Use when you need to import large volumes of vectors from external storage. Returns an impo
  • Update Vector — Tool to update a vector in Pinecone by ID. Use to overwrite vector values and/or metadata. Supports bulk updates via metadata filters.
  • Upsert Records to Namespace — Tool to upsert text records into a Pinecone namespace. Use when you need to add or update records with automatic text-to-vector conversion.

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