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Perceptivity Labs

Right now, somewhere, a buyer is asking AI

“which car should I buy?”

Also: which card. Which hotel. Which serum. Millions of buying decisions a day, asked in private.
Perceptivity Labs

And the machine answered.

It named one brand.

Not ten blue links. One recommendation, delivered with confidence.
Perceptivity Labs

Everyone else?

Never mentioned.

Not ranked lower, absent from the answer. In roughly one answer in five, no brand is named at all. Illustrative · from category scans.
Machine perception is measurable, and what can be measured can be shaped

Make sure it recommends you.

Perceptivity Labs · AI perception systems

Shape how AI perceives your brand.

Sense measures how AI and social see you. Axon holds your brand truth. Studio creates the response and proves the lift. One closed loop for model-mediated markets.

The neutral referee · independent of media, agency, and suite
01 / Research thesis

AI is becoming the interface between markets and brands.

The internet was built for human navigation. AI systems now interpret it on behalf of buyers. Discovery, evaluation, recommendation, model-mediated. Brands need governed systems for machine perception.

02 / Coverage

Everywhere your buyer asks.

The large answer engines, retail and vertical AI surfaces, and the social threads that teach them, in every language your buyers use, not just English.

ChatGPTGoogle GeminiGoogle AI OverviewsPerplexityClaudeMicrosoft CopilotGrokMeta AIAmazon RufusDeepSeek
Coverage depth varies by engine · method, in the open →
03 / Products

Three modules. One closed loop.

01 · Measure
Sense

How answer engines and social see the brand, by engine, intent, language, and region. Opens on what changed, ends at a suggested action. Sense never executes.

Explore Sense →
02 · Govern
Axon

The brand truth every module reads, page-cited registers and an approved-facts library owned by brand and legal. Nothing enters Axon lights-out.

Explore Axon →
03 · Create
Studio

The governed response from the Sense handoff, strategy cited to approved facts only, through the gate, then the measured lift. Nothing publishes without a named approver.

Explore Studio →
Keep scrolling to move through the modules
04 / The loop

Brief. Handoff. Gate. Measure.

I · BriefSense finds the move, grade, CI, sample size. Not a vibe.
II · HandoffOpens written, in Studio, or to Jira, Slack, Email. You choose who executes.
III · GateApproved facts only · brand critic · claims linter · IP scan · C2PA · named approver.
IV · MeasureProximal lift with a CI, written back to the decision log.
Then it starts again
05 / The decision log

Every decision, on the record.

Date, trigger, action, owner, measured outcome. What you show leadership at quarter end.

Jul 02Answer-share drop caught → Studio · +1.8 pts · CI ±0.6
Jun 18Social SoV gap flagged → Jira · gap closed 40% · CI ±9
Jun 03Unsupported claim → held at the gate · blocked
Illustrative sample · we don't claim your revenue, we prove every decision
06 / Share of Model

The share of answers that name you.

58%Category leader
31%Rival
14%You
22%Not named at all
Illustrative · reported with confidence intervals, by engine, intent, language, region
07 / The referee

The measurer doesn't grade its own homework.

No mediaWe don't sell the ads we'd be reporting on.
No agencyWe don't produce the creative we grade.
No suiteNot bundled with the stack that sells you the seats.
Early deployments run personally by the founding team
08 / Proof

Anatomy of a move.

Illustrative · a paint brand
Dropped from the “best exterior paint” answer
Sense caughtChatGPT stopped naming the brand in 3 of 12 buyer phrasings. B− ▼ · CI ±0.6 · n=120
ResponseAn ownership-proof page, cited to approved facts, through the gate, a named approver signs.
Measured lift, written back to the decision log. +1.8 pts answer share · CI ±0.6
Illustrative · an EV challenger
A rival gained voice in the review threads
Sense caughtCompetitor Social SoV climbing in long-form reviews. C ▼ · CI ±9 · n=340
ResponseA reviewer-response brief, filed to Jira for the social team to run.
Measured lift, written back to the decision log. Gap closed 40% · CI ±9
Illustrative · a skincare brand
A draft claim the facts didn't support
Sense flaggedA results claim with no approved fact behind it.
GateHeld at the governance gate. Not published.
Outcome, and the missing fact added to Axon, so the next draft can stand. Blocked
Keep scrolling to move through the examples
Illustrative anatomies · real named case studies land in Wave 2, from live pilots
09 / Questions

Questions, answered.

01
What do you measure?

Share of Model, the share of category answers that name, cite, or trust your brand across engines, intents, languages, and regions, plus Social SoV in the feeds those models learn from. Every number carries a confidence interval and a sample size.

02
Is this SEO?

No. SEO optimizes for ranked links on a results page. We measure and shape how answer engines name and recommend your brand inside the answer itself, a different surface, with different mechanics.

03
How are you independent?

We don't sell the media whose performance we'd report, we don't run the agency whose creative we'd grade, and we're not bundled in a suite that sells the seats. The number has no budget riding on it.

04
Do you train on our data?

No. Client content runs and reports your engagements; it never improves a shared model. Each tenant is isolated, and nothing enters Axon or publishes from Studio without a named human approver.

05
How do we start?

A free, founder-reviewed scan within 48 hours; then a fixed-scope eight-week pilot; then a platform engagement shaped with you. No self-serve and no published prices, we quote against a pilot, not a template.

Keep scrolling to move through the questions
10 / Bring your own agent

Let your AI read us first.

The product philosophy, applied to us: a governed, page-cited brief your assistant can read. Point your agent at it and ask anything.

Read https://perceptivitylabs.com/llms.txt and tell me what Perceptivity does, who it's for, and how a pilot works.
Begin

Measure machine perception. Govern the response.

Start with a founder-reviewed read of your category, the answer surfaces that matter, and the perception gaps worth addressing.