An honest comparison
monō vs Glean
Glean finds the answer. monō does the work.
Our honest position
Glean is a strong enterprise search and assistant layer, it helps people find and ask across company knowledge. monō goes past retrieval to execution: agents that take action, run processes and ship outcomes, with governance and your own models.
| Dimension | Glean | monō |
|---|---|---|
| Core job | Find and answer across knowledge | Execute work autonomously |
| Action | Surfaces information | Agents take action + ship outcomes |
| Model choice | Managed models | Model-agnostic |
| Data residency | Vendor-managed | Your cloud, inference-only |
| Governance | Search permissions / governance | Eval + monitoring on actions |
| Cost to run | Per-seat enterprise licence | Harness efficiency + BYO keys |
| Compounds over time? | No memory that compounds across your tools and teams | Yes, one memory across your tiles, people and time, inside your tenant |
Core job
Glean: Find and answer across knowledge
monō: Execute work autonomously
Action
Glean: Surfaces information
monō: Agents take action + ship outcomes
Model choice
Glean: Managed models
monō: Model-agnostic
Data residency
Glean: Vendor-managed
monō: Your cloud, inference-only
Governance
Glean: Search permissions / governance
monō: Eval + monitoring on actions
Cost to run
Glean: Per-seat enterprise licence
monō: Harness efficiency + BYO keys
Compounds over time?
Glean: No memory that compounds across your tools and teams
monō: Yes, one memory across your tiles, people and time, inside your tenant
Cost-to-run is illustrative, same outcome, materially fewer tokens; with your own API keys, your rates, no markup. All marks belong to their owners.
No FUD
When they're the right call.
- Your primary need is enterprise search and Q&A over company knowledge.
- You want a horizontal assistant, not autonomous execution.
- You’re not ready to put agents on operational work.
If you specifically need leading enterprise search and knowledge Q&A, Glean is purpose-built for it.
The architecture difference
Three decisions they can't retrofit.
Sovereign by architecture
Inference-only. Your cloud, your keys, the data never builds anyone else's product.
Model-agnostic
Frontier, open-source, fine-tuned, swap models without rewrites.
Your own API keys
Your lab accounts, your negotiated rates. We never mark up your tokens.
In depth
The fuller picture.
What Glean is built for
Glean is a strong enterprise search and assistant layer. It helps people find and ask across company knowledge, with permissions respected. If your primary need is retrieval and question answering over what the company already knows, Glean is purpose-built for it.
From finding the answer to doing the work
monō goes past retrieval to execution. Agents take action, run processes and ship outcomes, with eval and monitoring on every step, using your own models inside your cloud. Search surfaces information; monō acts on it. When you are ready to put agents on operational work, that is the line between the two.
FAQ
Questions, answered straight.
- Is monō an enterprise search tool?
- Not primarily. monō can read across your knowledge, but its job is to act, run processes and ship outcomes. Glean is focused on search and question answering.
- Can the two work together?
- Yes. Retrieval can feed agent work. monō is the layer that turns a found answer into a completed, governed task.
- Where does our knowledge stay?
- Inside your cloud. monō is inference-only, so your knowledge is never co-mingled or used to build anyone else's product.
- When should I choose Glean?
- When your core need is leading enterprise search and knowledge question answering rather than autonomous execution, Glean is built for exactly that.
See it on your own use case.
Your use case, live on the platform, beside whatever you're evaluating.