Gyld vs a vector database

The whole context pipeline vs. the storage layer underneath it

What is a vector database?

A vector database (such as Pinecone, Weaviate, or Postgres with pgvector) stores embeddings and runs similarity search over them. It is infrastructure: it answers "which vectors are closest to this query," but it does not ingest your apps, create embeddings, enforce permissions, or serve results to agents.

Gyld vs a vector database: how they compare

A vector database is one component of a context system. Gyld is the complete context layer: it ingests your company data, chunks and embeds it, runs retrieval, enforces access control, and exposes the result to agents over MCP. The vector database is the storage Gyld manages for you.

Gylda vector database
ScopeEnd-to-end context layerStorage + similarity search only
Ingestion from appsBuilt inNot included
Embeddings pipelineManagedYou build it
Permissions & isolationPer-company, per-user visibilityNot a database concern
Agent accessMCP servers any agent connects toYou build the serving layer
Who it is forTeams who want company context in their agentsEngineers building retrieval systems

When to choose Gyld

  • You want company knowledge usable by agents without assembling the surrounding pipeline
  • You need ingestion, permissions, and MCP serving, not just vector storage
  • You want a managed system instead of operating infrastructure

When to choose a vector database

  • You are building a custom application and need raw vector storage as one piece
  • You have specialized indexing or ranking requirements at the storage layer
  • You already run the ingestion, embedding, and serving layers yourself

Frequently asked questions

Does Gyld replace a vector database?

For company-knowledge use cases, yes. Gyld includes managed vector search as part of its pipeline, so you do not provision or operate a separate vector database to give agents company context.

What does Gyld add on top of a vector database?

Ingestion connectors for your apps, automatic chunking and embeddings, access control and multi-tenant isolation, source-cited retrieval, and MCP servers any agent can connect to — everything around the storage layer.

Give your agents real company context

Gyld is the business context layer for AI — connect your apps, build your company brain, and plug it into any agent over MCP.

More comparisons