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The most visible DLP tools on ChatGPT, October 2026

October 2026 · 15 questions asked in English, worldwide · ChatGPT · 19 answers read

Where engines disagree most

One engine

This page reads ChatGPT only. Set Engine to All to compare them.

Brands

Rank Brand Heralded Score Mentioned Recommended By engine Mentioned by Change
1 Microsoft Purview US 71 , range 48–83 79% 36% None First reading
2 Netskope US 41 , range 29–63 39% 14% None First reading
= 3 Forcepoint US 22 , range 4–45 21% 0% None First reading
= 3 Zscaler US 22 , range 4–45 21% 0% None First reading
5 Broadcom Symantec DLP US 9 , range 1–42 14% 0% None First reading
– Chrome Enterprise US Too few answers 0% 0% None First reading
– Cisco Secure Email US Too few answers 0% 0% None First reading
– Cloudflare US Too few answers 0% 0% None First reading
– CurrentWare CA Too few answers 0% 0% None First reading
– Cyberhaven RO Too few answers 0% 0% None First reading

“=” marks brands whose score ranges overlap, so the test cannot separate them. Every brand named in at least three answers is ranked. By engine has one dot per engine (ChatGPT, Google AI Overviews, Gemini and Google AI Mode), darker the more often it names the brand.

Most cited sources

Rank Source Type Cited in Engines Pages cited Brands its pages mention
11Withheld. Run a full Snapshot to see it.
12Withheld. Run a full Snapshot to see it.
13Withheld. Run a full Snapshot to see it.
14Withheld. Run a full Snapshot to see it.

The questions, and who wins each

QuestionLanguageWins it
how do companies prevent data leaks across email, browsers, and file storage English No brand recommended
can one policy protect sensitive data on laptops and in cloud services English No brand recommended
what can replace manual checks for employees sharing confidential files English No brand recommended
how can we replace separate rules for email and endpoint data leaks English No brand recommended
what can replace blocking every file upload to prevent data leaks English No brand recommended

Each engine's top three

Method

Each month Heralded asks every engine the same buyer questions, twice each, and reads every answer. An answer counts 0 for a brand it leaves out, 50 for a brand it names and 100 for a brand it recommends, and the Heralded Score is built from those. A brand named in at least three answers gets a score and a place.

How the leaderboards are measured