Not a paid review. No affiliate links. Just what I actually found.
Glean
What it does: Enterprise search across all your connected apps — Slack, Notion, Google Drive, Jira, all of it.
What I liked: The breadth is real. One query actually pulling from five systems and returning coherent results is impressive the first time you see it.
What annoyed me: Setup requires IT involvement for every connector and enterprise orgs have a lot of connectors. Also expensive. Like, really expensive for what it is.
The access control question: Respects source system permissions at the application level. Have not been able to confirm how it behaves at the retrieval layer for edge cases.
Score for knowledge retrieval: 7/10
Score for enterprise-readiness: 8/10
Would I recommend it: For large enterprises with budget and IT resources, yes. For everyone else, probably not.
Guru
What it does: Structured knowledge base with AI search on top of curated cards.
What I liked: When the knowledge base is well-maintained, it is extremely reliable. Source citations on every answer. Conservative about what it knows.
What annoyed me: Requires someone to care. The curation burden is real and most teams underestimate it. If the knowledge base gets stale, the AI gets stale too, and there is no automatic signal that this has happened.
The access control question: Card-level permissions work fine. Not designed for document-level sensitive data.
Score for knowledge retrieval: 8/10 when maintained, 5/10 when not
Score for enterprise-readiness: 7/10
Would I recommend it: If you have someone who will own the curation long-term. Otherwise no.
Notion AI
What it does: AI on top of your existing Notion workspace.
What I liked: Zero setup if you're already in Notion. The writing tools are genuinely good.
What annoyed me: Confident wrong answers are too common on factual queries. Great for drafting, not reliable enough for policy lookup.
The access control question: Follows Notion's page permissions but edge cases exist. Found restricted content surfacing through indirect queries.
Score for knowledge retrieval: 6/10
Score for enterprise-readiness: 5/10
Would I recommend it: For content-heavy workflows yes. For HR/policy/compliance queries no.
PrivOS (https://privos.ai/)
What it does: Self-hosted AI workspace. Chat, files, knowledge base, agents, all running on your own infrastructure.
What I liked: The data residency story is clean and honest. Your data does not leave. Room-based isolation means access control is architectural rather than policy-based. Compared to filter-based approaches in the other tools, this is a fundamentally different security guarantee.
What annoyed me: Higher setup overhead than cloud tools. Not something you spin up in an afternoon.
The access control question: This is the strongest of the five. Isolation by design, not by configuration.
Score for knowledge retrieval: 7.5/10
Score for enterprise-readiness: 9/10 for security-conscious orgs
Would I recommend it: If data residency or access control is a real requirement, yes. If you need zero setup time and your data is not sensitive, look at the others first.
SearchUnify
What it does: Enterprise AI search with strong support/service desk focus.
What I liked: The intent classification for support use cases is noticeably better than general-purpose tools.
What annoyed me: Built for support teams. Trying to use it for general enterprise knowledge felt like using a specialist tool for a generalist job.
Score for knowledge retrieval: 7/10 for support, 5/10 for general use
Score for enterprise-readiness: 7/10
Would I recommend it: Only if your primary use case is customer support or service desk.
The honest summary: None of these is perfect. Pick based on what your actual constraint is: breadth of coverage, curation ease, data security, or vertical fit. The worst outcome is picking the most impressive demo and finding out what you actually needed six months later.
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