Why should you care?

Teams wanting zero vector ops choose Pinecone over self-hosted Milvus while AgentNest keeps the same IVectorStore interface.

See it live — copy this example

Paste into an ASP.NET Core 8+ / AgentNest project, then run with dotnet run (set your API keys in user-secrets).

// AgentNest.Infrastructure/PineconeVectorStore.cs
public sealed class PineconeVectorStore(PineconeClient client, IOptions<PineconeOptions> opt) : IVectorStore
{
    public async Task UpsertAsync(string tenantId, string id, ReadOnlyMemory<float> vector, string text, CancellationToken ct)
    {
        var index = client.Index(opt.Value.IndexName);
        await index.UpsertAsync([new Vector { Id = id, Values = vector.ToArray(),
            Metadata = new MetadataMap { ["tenant"] = tenantId, ["text"] = text } }], namespace: tenantId, cancellationToken: ct);
    }
}

What happened?

• PineconeVectorStore upserts with tenant namespace isolation and stores text in metadata for retrieval display.
• Follow the steps below — typing the code yourself is the fastest way to learn.

Practice next

1. dotnet add package Pinecone.Client.
2. Create index with dimension matching embedding model.
3. Register PineconeVectorStore when VectorStore:Provider=Pinecone.
4. Add metadata filter on document type during search.
5. Switch to serverless index spec in Pinecone console.

Remember

Pinecone provides managed vectors with namespace tenancy. build IVectorStore adapter in Infrastructure. Match index dimension to embedding output size.

CRM playbook hosting

AgentNest SaaS indexes 10k playbooks across 500 tenants on Pinecone.

Outcome: Per-tenant namespaces isolate vectors without separate Pinecone projects.