CentralAgent vs Glean
Glean is enterprise search with an assistant on top: it connects to the tools your company already uses and answers questions from what is already written down. CentralAgent targets the knowledge that was never written down: it captures meetings and agent sessions, structures them into agentic memory, and runs inside your private cloud. If your knowledge lives in well-maintained documents across many apps, Glean fits. If it lives in your veterans' heads and your agents keep starting from zero, CentralAgent was built for you.
Two different jobs
Glean describes itself as "Work AI that understands your company". It connects to the content your company already produces, documents, tickets, wikis, chat, and answers questions over that index with permissions respected. For what it does, it is a serious product, and this page will tell you plainly when it is the better pick.
CentralAgent starts where an index ends. Our 120 interviews with engineering leaders kept surfacing the same fact: roughly 80% of the context that makes a veteran valuable never reaches documentation, so no connector can index it. CentralAgent captures that context at its source, your meetings and your agent sessions, structures it into layered agentic memory, and deploys the whole system inside your private cloud.
Side by side
| Glean | CentralAgent | |
|---|---|---|
| Primary job | Search and assistant over content that already exists in your apps | Capture knowledge that was never written down and encode it as agentic memory |
| Knowledge source | Documents, tickets, chat, and other content reached through connectors | Meetings and agent sessions, captured live |
| Undocumented knowledge | Out of reach until someone writes it down | The core target: roughly 80% of veteran context never reaches docs, per our 120 interviews |
| Who can buy it | Sales-led; buyer reports put minimum commitments around 100 to 250 seats, with a median contract near $99k/year (Vendr) | Any team size; the 30-day trial starts from one setup call |
| Your coding agents | Assistant and agents run on Glean's own surface | Memory loads into the agents you already run, such as Claude Code and Cursor |
| Deployment | Managed service; see glean.com for current options | Inside your private cloud; your data never leaves it; no training on your data; SOC 2 in progress |
| Proof you can run yourself | Demo through their sales process | Reproducible benchmark: medians of 4 tool calls, 31s, $0.12 with memory vs 22 calls, 122s, $0.64 without |
| Getting started | Enterprise sales motion | 30-day free trial in your own cloud, deployed by our engineer on day one |
When to choose Glean
Choose Glean when your company's knowledge is mostly written down and the pain is finding it. The classic profile: a larger organization, content scattered across dozens of tools, a documentation culture that mostly works, and employees losing time to search. Permissions-aware answers across everything are a genuine relief there, and an index is the shortest path to an answer that already exists in some document. If that is you, Glean is the honest recommendation.
One practical note for smaller teams: Glean publishes no pricing, and procurement data from Vendr reports minimum user commitments that often start around 100 to 250 seats. If your team is under that line, the comparison may be moot before it starts.
When to choose CentralAgent
Choose CentralAgent when the answers your team needs are in people's heads, and increasingly in the agent sessions where those people work. The profile from our interviews: an engineering team running coding agents daily, a handful of veterans fielding the same questions on repeat, a wiki nobody quite trusts, and a hard requirement that company data stays inside your own cloud. You want new hires and agents to inherit context, and you want it measured: first veteran-grade answers inside week one of a pilot, against criteria agreed in writing.
Can you run both?
Yes, and some companies should: the products touch different layers. Glean makes what is written findable; CentralAgent captures what was never written. If you have to sequence them, an engineering team heavy on agents should capture first, because per our interviews the unwritten share is the larger one, and what you don't capture, you can't backfill.
Check the claims
The fastest way to judge us is the race demo: real infrastructure questions, same model with and without memory, medians shown above and reproducible. Then book your setup call to start the 30-day free trial in your own cloud. For the concepts, read what is tribal knowledge and how CentralAgent works.