Comparison
Gateco vs Glean
Glean is a closed-source enterprise knowledge search platform that crawls and indexes your SaaS tools. Gateco is a policy enforcement middleware that sits above your own vector databases. They solve fundamentally different problems.
| Capability | Gateco | Glean |
|---|---|---|
| Connects to your own vector databases Glean indexes its own data store; Gateco sits above databases you already operate | ||
| Fine-grained RBAC/ABAC/ReBAC policies Glean inherits source-system permissions; no custom policy conditions | partial | |
| Audit trail per retrieval (principal + resource + policy) | ||
| 12 vector DB connectors | ||
| Bring your own embedding model Glean controls the indexing pipeline | ||
| MCP server (Claude Desktop, Cursor) | ||
| Python + TypeScript SDK Glean has a REST API; no open SDK | ||
| Grounded answers (policy-filtered LLM synthesis) | ||
| Fail-closed on evaluation error Gateco denies on policy error; Glean behavior on error is not documented | ||
| Cross-connector unified policy model | ||
| SCIM v2 user provisioning | ||
| SOC 2 Type II | In progress (H2 2026) | |
| Self-host / on-premises Glean is cloud-only | roadmap (Q3 2026) | |
| Public pricing Glean is contact sales |
Glean indexes for you. Gateco enforces for you.
Glean is a complete knowledge search product. You connect it to Slack, Confluence, Google Drive, GitHub, and it crawls, indexes, and serves search results. Access control is inherited from the source systems — if you can read the Slack channel, you can read its indexed content in Glean. That model works when your AI access requirements are the same as your collaboration tool access requirements.
Gateco assumes you already have vector databases, an embedding pipeline, and likely a RAG application. What you need is a policy enforcement layer between that application and your data — one that evaluates principal identity from your IDP against classification policies you define, produces an audit trail, and fails closed on any error. Those are different requirements from what Glean solves.
When to use each — or both
Use Glean if you need a turnkey semantic search product over your SaaS collaboration tools with minimal engineering investment. Use Gateco if you're building or operating AI applications that retrieve from vector databases and need fine-grained access control, an audit trail, and policy management that your security team can own.
They can coexist. Some organizations use Glean for broad knowledge search and Gateco for high-sensitivity RAG pipelines (HR data, legal documents, financial records) where the compliance requirements exceed what inherited source permissions provide.
Start with Gateco
Free plan available. Connect a vector database in under 10 minutes.