# Pinecone & AI agent examples **URL:** \ **Category:** Ask for Help\ **Created:** [February 26, 2025, 4:08pm UTC](https://community.glideapps.com/t/pinecone-ai-agent-examples/80370 "2025-02-26T16:08:13Z")\ **Posts on this page:** 1\ **Showing post:** 5
**Author:** ![c0bbler](https://sea2.discourse-cdn.com/flex002/user_avatar/community.glideapps.com/c0bbler/32/68741_2.png) [@c0bbler](https://community.glideapps.com/u/c0bbler)\ **Post date:** [March 4, 2025, 7:49am UTC](https://community.glideapps.com/t/pinecone-ai-agent-examples/80370/5 "2025-03-04T07:49:21Z")
I am using the integration to upsert profiles into an index and then compare them for similarity, I can do a deeper dive when I get through the fully implemented end result. One important limitation of the Glide integration is lack of support for metadata. (of course if I’m wrong about this please correct me). This requires that I use [make.com](http://make.com) integrations instead of Glide’s native implementation, because metadata cannot be included in the text-based index body. I would love Glide to enable metadata support! Metadata is important for pre-filtering results when querying the index for vector similarity, in such a case where you don’t want to return results that are obviously not what the user wanted. For example, we would want to use pre-filter to restrict similarity results to metadata that fits preferences stored in the profile. If a user is looking for a specific set of circumstances when comparing values, the end resulting similarity should fall within the confines of those preferences. Note I am using indexes and not document search or assistant (yet). An update: Upon further investigation, [make.com](http://make.com) pinecone modules are pre-configured for storing vectors, not actually performing the embeddings, which means you need to select an embedding API (a model) in addition to storing the vectors. That means that the vectors themselves can be queried in a make scenario, but that embedding is managed separately which complicates the workflow compared to Glide’s integration. I filed a feature request for metadata support here: > [@Support metadata in Pinecone](https://community.glideapps.com/t/support-metadata-in-pinecone/80473): > > Hey team, Pinecone integration is awesome! Thanks a ton for giving us this functionality. As of this writing, there are 2 primary use cases for pinecone relative to storage, one for vectors and the other for documents. Assistants (as you have integrated) can be set up around stored documents and queried. However indexes, when data is upserted, can be used slightly more generically to query indexes based on semantics, lexical, and other query types to find vector similarity. I have found Glide’s… --- _[View the full topic](https://community.glideapps.com/t/pinecone-ai-agent-examples/80370)._