Key findings
- Of 51 public accounts, 11 discuss cross-app search and 10 of them are positive.
- 8 accounts discuss Glean's Assistant answers: 4 are positive and 4 are critical.
- Of 6 accounts on accuracy, 5 raise concerns. Internal jargon misleads answers, sales-process answers contain errors, and older material sometimes ranks above current results.
- In Slack, Glean privately told an employee that a real fire alarm was a scheduled test.
- Of 23 accounts that discuss Glean Agents, the APIs, or the MCP server, 19 are positive. Critical accounts include GitHub reports of Glean's SDKs and MCP server failing during setup.
- Glean's own published tests, run on its internal data, prefer Glean over ChatGPT, Claude, and Claude Cowork. Neither covers Microsoft 365 Copilot, Notion AI, or Rovo.
Test Glean on 100 or more of your own questions before you sign or renew. Public accounts praise its search across apps and split on its Assistant answers, and the wrong answers they report trace to casual or stale indexed content.
Search is where accounts agree
Developers and employees describe Glean beating Atlassian's own search for Jira and Confluence and finding documents across Slack, Drive, GitHub, and source code from one box. At Abnormal, Andy Chen calls it excellent at finding documents and used it heavily while onboarding. A Starburst solution architect uses search and chat across Slack, Confluence, and email every day.
Answers depend on what is indexed
Critical accounts trace wrong answers to their sources. An engineer found Glean-drafted docs misleading four times in five because internal terms differed from common usage. A Carta account executive reported wrong sales-process answers and documents missing after the move from Guru. An account manager found older material ranked above current results.
Chen separates retrieval from deciding what an assistant should answer. Glean finds matching documents, and no document tells it to send data-retention questions to security. A data team member restricted an agent to specific knowledge sets to reduce hallucinations and still checks output manually.
How to test it yourself
Glean has published two comparisons, both on its own internal data. In February 2026, four graders judged answers to about 280 queries from Glean's internal deployment. When they had a preference, they picked Glean as correct 1.9 times as often as ChatGPT and 1.6 times as often as Claude. In August 2026, graders preferred Glean over Claude Cowork 78% of the time across 180+ responses, at US$0.58 per task against US$2.98. Glean ran on automatic model routing and Cowork held to Sonnet 5. Run the same kind of test on the products you are choosing between.
- Write 100 or more real questions from support, sales, HR, and engineering, with the expected answer and source for each.
- Include questions with no answer, to check that Glean says so.
- Run them on each candidate connected to the same sources, and grade blind.
- Re-run after seeding Answers and verified documents, to measure what content work changes.
Methodology
GILD read 51 public accounts published from January 1, 2025 to September 22, 2026 and recorded the themes each discusses. They include 14 PeerSpot and TrustRadius reviews from named roles, an engineering account from Motive, and 6 GitHub issues with reproductions from developers building on Glean's APIs and MCP server. On October 25, 2026 GILD read Glean's two published evaluations and The AI Economy's report on the second, and searched for outside comparisons with Microsoft 365 Copilot, Notion AI, and Rovo. Every comparison figure here is Glean's own, linked in Sources.
Products in this piece
Sources
- Official documentation
- 7
- Public source
- 7
- Glean docs: About connectors
- Glean: Enterprise AI assistant
- Glean docs: Populate content
- Glean docs: Supported LLMs
- Glean docs: Glean Enterprise Flex pricing
- Andy Chen: The Enterprise Context Layer (Mar 10, 2026)
- Hacker News comment on Glean-drafted docs and internal terminology (Jun 3, 2025)
- TrustRadius review by Savannah Hair, Carta: Glean vs. Guru (Nov 5, 2025)
- Tagir Valeev on Mastodon: Glean in Slack calls a real fire alarm a scheduled test (Feb 12, 2026)
- Sravani Kakaraparthi: Automating dbt Documentation with a Glean agent (Dec 30, 2025)
- PeerSpot review by Ambsingh Singh, LinkedIn (Mar 15, 2026)
- Glean blog: Not all enterprise context is created equal: Glean results preferred ~2x more often than ChatGPT's company knowledge (Feb 12, 2026)
- Glean blog: Right-sizing intelligence: Glean saves 81% on token costs and is preferred 78% of the time versus Claude Cowork (Aug 26, 2026)
- The AI Economy: Glean's Bet: Enterprise AI Runs on Context (Ken Yeung, Aug 30, 2026)