qbrin vs Glean

What each product is

Glean positions itself as “Work AI that understands your company”, with three pillars: Assistant and Search, Agents, and a governance layer called Glean Protect. It advertises 275+ app connectors with permissions-enforced search, answers delivered as “cited insights”, support for 35+ LLMs, and certifications including ISO 42001, HIPAA, SOC 2 Type II, ISO 27001, GDPR and TX-RAMP Level 2. Independent coverage reports Glean crossed $200M ARR, built on a permissions-aware knowledge graph.

qbrin is enterprise AI search over email, files, Slack and tickets. The differentiator is the trust layer: verification gates run on every answer, every claim must be grounded in a citable source, and when the evidence is not there qbrin abstains instead of generating something plausible. Per-user access control is enforced at retrieval time, so an answer is only ever assembled from documents the person asking is allowed to see.

Feature comparison

The real difference: what happens when the answer is not in your data

Most enterprise AI search products, Glean included, are built to maximise the chance of producing a useful answer, and they attach citations to what they produce. qbrin is built around the opposite failure mode: the answer that looks right, reads confidently, cites something, and is wrong.

qbrin’s trust layer treats every answer as a claim to be verified before it reaches the user. Each numeric value, each entity, and each cited source passes through verification gates. If a citation does not exist, or does not actually support the sentence it is attached to, the answer is blocked. If the evidence is incomplete, qbrin abstains and tells you what is missing.

In our benchmarks (our own suites, run only on qbrin; we have not run a head-to-head benchmark against Glean and make no comparative performance claim):

• 0 false accepts across our trap-question suites: questions about entities that do not exist in the corpus, where the correct behaviour is to refuse.
• 211/211 fabricated-source citations caught in a 710-specimen suite built from real text across 18 domains.
• 88% recall@20 on our retrieval benchmark, because a trust layer is only useful if retrieval finds the evidence in the first place.

Where Glean is genuinely strong

An honest comparison should say this plainly. Glean has hundreds of connectors, a permissions-aware knowledge graph refined over years, an agent platform that large companies use at scale, a long certification list, and reference customers with tens of thousands of seats. If you need one platform to cover search, assistant and agent automation across your whole stack, and you have the budget for a sales-led enterprise contract, Glean is a strong default and you should evaluate it seriously.

What qbrin does not have

qbrin does not have Glean’s deployment history, customer list, connector catalogue or agent-marketplace breadth. We are a young product with a narrow, deliberate focus: search over email, files, Slack and tickets, with answers you can act on without re-checking them. If that focus matches your problem, the trade is worth it. If you need 200+ connectors on day one, it is not, yet.

Who should pick which

FAQ

Is qbrin a drop-in replacement for Glean?

No. Glean is a broader platform; qbrin covers enterprise search over email, files, Slack and tickets with a verification layer. If your Glean usage is mostly “find and trust the answer”, qbrin covers that job. If you rely on Glean’s agent builder or long-tail connectors, it does not.

Doesn’t Glean also cite sources?

Yes. Glean describes its Assistant output as “cited insights” and its search as permissions-enforced. The architectural difference is what happens on failure: qbrin’s gates verify that each citation exists and supports the claim, and block or abstain otherwise. We publish the benchmark method we use to test that behaviour.

How much does Glean cost?

Glean does not publish pricing. Third-party analyses estimate roughly $45–75 per user per month with around 100-seat minimums and add-ons on top; treat those as estimates and confirm with Glean.

Has qbrin benchmarked against Glean directly?

No, and we will not imply otherwise. Our published numbers come from our own suites run on qbrin alone. What we compare here is architecture: cited-or-abstain with verification gates versus a platform that optimises for answer coverage.

Try the abstention test

Bring three questions you know your documents cannot answer, and three they can. Connect your sources and watch what qbrin does with each.

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