A team working through a brief in daylight

Customers

For the brands AI is now recommending — or leaving out

Besaid is the team that gets brands seen — and recommended — in AI answers, end to end: we measure, we fix, we prove it. This is how we define a good outcome, and what one looks like.

Who we serve

Any brand a buyer now discovers by asking an AI first — agencies, institutions, professional firms, clinics, software. We went deepest first in international education; the outcome definition below is the same wherever the shortlist forms.

See how we do this for international education →
  • Agencies & consultancieswhere the shortlist is won or lost
  • Institutions & programshigh-stakes choices researched for months
  • Cross-border brandsseen across languages and engines

01Measure

How we measure success

A visibility number only means something against a baseline, on the questions that actually convert, with the sample size that backs it. We hold our own work to four tests.

The four tests
  • Baselinea fixed, replayable T001
  • Questions that convertcategory, not your own name02
  • Honest attributioncorrelation called correlation03
  • Board-ready evidenceverbatim, both sides, sealed04
(01)

Baseline before we touch anything

We sample your visibility across engines and markets first, and store it verbatim. Every later claim of improvement is measured against a fixed, replayable starting point — not a memory of how things used to look.

(02)

The questions that convert, not vanity keywords

Being recommended when a buyer asks 'which provider can we trust?' wins you pipeline — showing up for your own name does not. We track the questions that decide the shortlist, in the languages buyers ask them.

(03)

Attribution, shown honestly

You see exactly what we did, when we did it, and how AI answers changed afterwards. We show correlation and call it correlation — AI answers shift for many reasons, and we never claim credit the data can't back. Pretending otherwise is how this market lost its credibility.

(04)

Evidence your board will accept

The deliverable isn't a slide with a bigger number. It's the same question, same engine, replayed before and after — the AI's exact words on both sides, in a tamper-proof record leadership can quote with confidence. That is what survives scrutiny.

02Outcomes

What a good outcome looks like

The scenarios below are representative illustrations, not results from named clients. The numbers are drawn to be plausible for the categories shown; your baseline and trajectory will differ. As real engagements complete, we'll replace them with real before-and-after evidence.

DeepSeek2026-05-14n=120sha:4e7b…a02fIllustrative

Invisible when the question is asked in another language

A professional-services firm with strong Google rankings finds it is absent when buyers ask in their own language for a trustworthy advisor — the exact moment the shortlist forms.

Visibility θ · DeepSeek + Qwen

Before

Named in ~6% of DeepSeek and Qwen answers (n=120 each); two competitors named first; the firm's own site never cited.

After

Within one measurement cycle, the firm goes from barely mentioned to named in nearly 1 in 3 AI answers — and its own website starts being quoted as a source.

Share of AI answers naming you↑ higher is better
Before6%
After31%

barely mentioned → named in ~1 of 3

AI Overviews2026-05-21n=216sha:1c9d…7b60Illustrative

Confidently described with the wrong facts

A B2B software vendor is repeatedly summarized by AI with an outdated pricing tier and a feature that no longer ships — a hallucination that quietly steers buyers wrong.

Hallucination rate + sentiment

Before

The stale facts appear in roughly a third of sampled answers; sentiment reads 'cautious' where sources conflict.

After

Once official facts are published where AI can find and trust them, the outdated claims fade from later answers — and AI's tone turns clearer.

Stale-fact rate in answers↓ lower is better
Before33%
After5%

cautious tone → positive tone

Perplexity2026-06-02n=194sha:8a30…d5e1Illustrative

Out-shouted by aggregators and forums

A foundation program's own voice is missing from AI answers — engines cite ranking sites and forum threads instead, and the institution is listed last when listed at all. (Education — our deepest vertical.)

Owned-territory share + position

Before

AI almost never quotes the program's own website; when the program appears at all, it sits near the bottom of the list.

After

As your own pages become the clearest, most authoritative source to cite, AI quotes them more often — and lists the program higher up the answer.

Your own site as a cited source↑ higher is better
Before8%
After41%

listed last → near the top

Evidence you can show your board

  • An evidence pack your board or procurement team can verify line by line — not a black-box score
  • The AI's exact words, before and after, in a tamper-proof record
  • Every result tells you how many AI answers we checked — no cherry-picked wins
  • Every engine measured side by side, in one report

Find out what AI is telling your applicants — before your competitors do.