The AI interface is flashy, but the real fight is for the plumbing
If every company is racing to add a chatbot, the quieter advantage is who controls what the bot can actually do. Glean's pitch is that the durable moat isn't 'a nicer chat UI,' it's the layer beneath the interface: identity, access controls, connectors, indexing, and workflow execution.
Why this layer is suddenly strategic
Enterprise AI isn't blocked by model quality as much as by trust and integration friction.
- Teams want answers that respect RBAC/ABAC rules, not a clever hallucination that accidentally leaks HR docs.
- They want actions that work across toolscreate a ticket, update a doc, kick off an approvalwithout building a dozen brittle one-off integrations.
- And they want to swap models as pricing/performance shifts, without ripping out the whole stack.
Glean's angle: own the orchestration, not the model
What 'the layer beneath' usually means in practice:
- A connector mesh that normalizes data from Slack, Google Workspace, Microsoft 365, Jira, Confluence, Salesforce, etc.
- A retrieval system tuned for enterprise reality: permissions-first, auditability, freshness, and relevance.
- An action framework that turns intent into execution (the part everyone calls 'agents' now), with guardrails and logging.
What to watch next
- Whether Glean can become the enterprise default, or whether suites (Microsoft/Google/Salesforce) bundle this layer into existing contracts.
- Whether buyers standardize on one vendor for search + agentic workflows, or split it (best-of-breed retrieval, separate automation).
- How fast governance features maturebecause in the enterprise, 'agentic' without controls quickly becomes 'unshippable.'