Glean and Sentrely live in the same broader category — “AI for the enterprise” — but they solve completely different problems and target different roles inside the buying organization.
Glean answers a question your knowledge worker has. Sentrely governs an action an autonomous agent takes. One reads, the other writes; one serves humans, the other supervises AI.
What Glean Is
Glean is enterprise search and AI work assistant. It provides:
- Indexed search across 100+ enterprise apps (Slack, Drive, GitHub, Confluence, Salesforce, Jira, Notion, etc.)
- Permission-aware retrieval — users only see results they have access to
- An AI assistant chat that synthesizes answers across that knowledge base
- Glean Agents — task-specific AI assistants for things like onboarding, IT helpdesk, sales enablement
- Workplace search analytics and content gap insights
The typical Glean buyer is a 500+ person company struggling with knowledge fragmentation. The KPI is “time to answer” for employees.
What Sentrely Is
Sentrely is a control plane for autonomous AI agents — the Claude Code, Cursor, and Codex agents that engineering, ops, and growth teams are increasingly running in production. It provides:
- Policy-based RBAC — what AWS actions, git repos, APIs each agent can touch
- Full audit trail of every tool call, conversation, and approval
- Human-in-the-loop gates — risky operations require Slack/Telegram approval
- Multi-provider routing (Claude, OpenAI, Cursor, Codex) with automatic failover
- Cost controls — per-agent token budgets, rate limits, spend alerts
The typical Sentrely buyer is an engineering team that has adopted Claude Code or Cursor and needs operational controls before agents touch production. The KPI is “incidents prevented per quarter” and “time-to-audit-compliance”.
Where They Overlap (And Where They Don’t)
There’s a thin slice of overlap: both involve AI, both touch enterprise data, both need RBAC. But the RBAC concerns are different:
- Glean RBAC = “this user can see this Drive folder”
- Sentrely RBAC = “this AI agent can call s3:PutObject on this bucket but not s3:DeleteObject”
The first is about information access. The second is about action authorization.
When You Need Both
Increasingly common in 2026: an autonomous agent running through Sentrely calls Glean as its knowledge retrieval tool. The agent asks Glean “what’s our refund policy” with a permission scope tied to the user who triggered the workflow; Glean returns the right answer; the agent then takes an action (issue refund, update CRM); Sentrely policy-checks and audits that action.
In this stack: Glean is the brain (knowledge), Sentrely is the conscience (governance). They compose naturally.
When You Don’t Need Sentrely
If your AI usage is bounded to Glean’s chat and Glean Agents — humans asking questions, AI synthesizing answers from your indexed knowledge — Glean’s built-in controls are likely sufficient. You only need Sentrely once your AI starts taking actions on systems Glean doesn’t manage.
When You Don’t Need Glean
If your AI agents already know what they need (because the prompts give them the context, or because they’re working over a known codebase), you may not need enterprise search at all. Sentrely doesn’t replace Glean’s knowledge retrieval, but if knowledge retrieval isn’t your bottleneck, you can skip it.
The Bottom Line
Glean is for knowledge — read-side AI that answers questions across your company’s data. Sentrely is for agents — write-side AI that takes actions on your company’s systems. Different categories, complementary purchases.