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Besaid vs Profound
Profound is an enterprise self-serve console for AI visibility, and one of the first tools in the category. Here is where Besaid takes a different path: an evidence chain you can audit, every engine — the Chinese ones included — treated as an equal, and the optimization work delivered rather than left to you.
What Profound is
- →An enterprise-grade self-serve analytics console for AI visibility.
- →Broad coverage of the major global engines.
- →One of the first tools in the category.
Where Besaid is different
- DeliverySelf-serve toolDone for you
- Visibility layersOne scoreRetrieved · Cited · Recommended
- Self-applied GEOProduct marketing sitellms.txt + structured pages
- What you getScores & chartsVerbatim answers
- Conversation depthAggregate metricsFull answer, replayed
- Engine coverageMajor global engines25 · Global + China
- Sample sizeNot stated publiclyShown on every %
At a glance — where Besaid differs. The detail, and a neutral description of Profound, is below.
A self-serve tool your own team runs.
We do the optimization ourselves — and show you what each action changed in the AI's answers.
Visibility commonly reported as a single aggregate figure.
Three layers kept apart — Retrieved, Cited, Recommended — so the blocked gap is visible.
A marketing site for the product, not necessarily structured for answer engines to quote.
We publish llms.txt, clear definitions, and machine-readable structure — the same owned-media discipline we sell.
Visibility scores and trend charts to read yourself.
Every number opens into the AI's actual words — proof you can put in front of a board.
Metrics aggregated across prompts.
Behind every number, the full conversation — replayed, with your brand highlighted, kept tamper-evident.
Broad coverage of the major global engines.
Every surface your buyers use — 25 in all: the full global set plus DeepSeek, Doubao, Qwen, Kimi, Tencent Yuanbao, Ernie Bot, Zhipu, Quark and the rest of the China set — measured to one standard, with 20 more on the roadmap.
Its public numbers don't state the sample size behind them.
Every percentage we publish shows its sample size — you always see the denominator.
These contrasts are drawn from each vendor's public materials (July 2026) and describe differences in approach — not a verdict on any product. A neutral description of each is above; products evolve, so check their current docs.
Comparison based on public materials as of July 2026; products evolve — check their current docs.
Which one fits
Choose Profound if
You'd rather run a self-serve dashboard yourself, and you're not looking for the work delivered, verbatim proof, or the Chinese engines.
Choose Besaid if
You need to prove every number with the AI's own words, your audience asks across languages, and you want the optimization delivered — not just measured.
