India's AI answer layer

Be the brand names

Your buyers ask AI — in Hindi, English, Hinglish. It names one brand. Perceptivity makes sure it's yours.

Free · 60 seconds · scanned across India's languages, live

01 / The shift

Buyers don't compare anymore. They ask.

One question, one answer, one recommendation. If your brand isn't in the answer, the buyer never finds you.

How buying used to work

They compared

Your buyer opened a dozen tabs, read the reviews, built a shortlist. You were in plain sight — and could earn your place.

How buying works now

AI decides

Your buyer asks one question and trusts one answer. If it doesn't name you, you're off the list — and you never see it happen.

A third of category research now starts with AI. Brands that aren't recommended get left behind.

A buyer asks
02 / The blind spot

You can't see it happen. Your buyers can.

Every day, AI tells your buyers which brand to pick. You don't get a report. You just lose the sale. Here's what that looks like:

Left out
Buyer asks
“Best running shoes for flat feet?”
Names three competitors in a tidy list. Your brand never comes up.
You never made the shortlist
Out of date
Buyer asks
“Is there a no-fee version of this card?”
“It still carries an annual fee.” You dropped that fee a year ago.
Judged on old information
Out-positioned
Buyer asks
“Your brand or the rival — which is better?”
“Most reviewers prefer the rival for value.” In your own comparison.
Beaten in your own comparison
03 / How it works

One platform for AI visibility.

See what AI says about your brand. Understand why. Change it.

I

Monitor

See how AI represents your brand — every major engine, region and language.

II

Diagnose

See the sources, citations and claims behind every answer. Know why you're named — or missed.

III

Shape

Fix what's wrong, fill what's missing, and watch the answer change.

Four steps, every quarter.

Forecast each move, make it, measure the lift. Numbers your board can read.

Step 01 · Sense

See what AI says today

Every engine, every buyer question, every claim — in one view.

Step 02 · Simulate

Model the move first

Rank each move by expected leverage before you spend.

Tier-1 citation
+3.8
Comparison piece
+2.4
Page refresh
+1.1
Step 03 · Act

One priority queue

One list for your team, agencies and partners — with owners and deadlines.

Knowledge graph fix
Comparison rewrite
Trusted-source placement
Review-site cleanup
Step 04 · Learn

Prove what moved

Predicted vs actual lift after every action.

Before
0/6
After
4/6
~⅓
of category research
starts with AI
10+
answer engines
tracked
1
defensible number
for the board, each quarter
Every answer engine that matters
ChatGPT
Google Gemini
Google AI Overviews
Perplexity
Claude
Microsoft Copilot
Grok
Meta AI
Amazon Rufus
DeepSeek

Coverage depth varies by engine · retail-AI surfaces in expanded rollout

04 / The engine

Built on two engines.

A query model tuned to how India asks, and a living map of your brand's reputation in AI.

8,000+India-tuned query profiles
Query profiles

8,000+ India-tuned query profiles.

We model how India actually asks — by language, city tier, income band, price sensitivity, voice vs typed — so the answers we track reflect your real buyer's question, not a generic English prompt.

  • Track perception across the queries your segments ask
  • Plan against the question patterns that convert
  • Act where it moves your priority segment
Brand knowledge graph

A living map of how AI sees you.

Every source, competitor and claim shaping your brand in AI — connected in one graph. Fix the right node, and the answer moves.

  • Every citation, rival and claim, linked
  • Pinpoint the source distorting your answer
  • Fix one node, shift the answer at scale
05 / The product

The loop, working.

See the answer AI gives today. Model what a campaign will change before you spend a rupee. Then ground AI in your own truth, so it quotes you instead of guessing.

Sense

See who AI names first.

Every buyer question, every engine, every morning. You wake up to who got named, who got cited, and what changed overnight.

Share of answer & position — who's named, who's cited, where you rank.
Languages & surfaces — Hinglish and regional, plus India's retail-AI assistants.
Overnight alerts — the morning a rival takes your place, you see it.
Who AI names first7 engines · India
Category leader28%
Rival two22%
You19%
Rival three13%
Not named18%

Illustrative · your category · model outputs, not a live query

Simulate Beta

Model the move before you make it.

Name the move — a comparison article, a PR placement, a pricing fix. We model its expected direction and relative magnitude per engine, so you spend on the highest-leverage action first. The model sharpens as your measured cycles accumulate.

Highest-leverage first — rank candidate moves by direction and magnitude, not a single number.
Predicted vs measured — every cycle sharpens the next forecast.
Candidate moves · expected leverageDirectional
Tier-1 citationHigh confidence
answer share+3 to +6pp
Comparison pieceHigh confidence
answer share+2 to +4pp
Page refreshModerate confidence
answer share+0.5 to +1.5pp
0+3pp+6pp

Illustrative · directional estimates, refined against measured outcomes each cycle

Author

Don't just watch the answer. Author it.

We turn your canonical truth — pricing, approved claims, specs, positioning — into the machine-readable sources AI engines actually ingest: structured data, knowledge-graph corrections, authoritative placements. Engines stop guessing because the strongest source in the room is now yours.

Try it → switch a source off on the right and see how the answer drifts when your truth isn't readable.
Publish Engines re-crawl Answers shift Answers shift over weeks, not clicks · typically 2–8 weeks per engine
Your source of truth5 / 5 synced
Current pricing
Approved claims
Product specs
Service & support
Positioning brief

↑ Toggle a source off to see what AI says when it can't read your truth.

Simulated answer · grounding mechanicAccuracy 100%
"What should a buyer know about your brand — price, quality and support?"
Grounded in your truth0 errors

Illustrative · grounding mechanic, not a live query

See what AI says Free · 60 seconds · your category
06 / India

Indian consumers don't ask in english

They ask in Hindi, Tamil, Hinglish — often out loud, by voice — across a dozen languages. Most tools only watch the English web. We watch the answer in every language and voice your buyers actually use.

i

Eleven languages, not one

We read the AI answer in Hindi, Tamil, Bengali, Marathi, Telugu, Kannada and Hinglish — not the English web every other tool watches.

ii

Most of India asks out loud

Voice and spoken AI search lead in regional languages. We track the answer your buyers hear, not just the one they read.

iii

Modelled on how India buys

Code-mixed queries, tier-2 and tier-3 search, price-first questions — measured the way your real buyer actually asks.

iv

Fix the sources India trusts

Models know Indian brands less well — so this is where they misname you. We map the publishers and creators they cite, so you know what to fix.

A buyer asks — out loud, in
English हिंदी தமிழ் বাংলা मराठी తెలుగు ಕನ್ನಡ Hinglish

Every global tool watches the English web. We watch the languages, and voices, your market buys in.

07 / The cost of waiting

Every quarter you wait, the gap is harder to close.

AI builds tomorrow's answers from the brands it already trusts today. The longer a rival owns the answer, the more it costs you to take it back.

Who AI names in your category
Illustrative · Decorative paints, India · 10 buyer questions
The category leadernamed in 6 of 10
A brand that waitednamed in 2 of 10

The brand AI names today becomes the brand AI quotes tomorrow.

08 / Who's behind it

We've been on both sides of the answer.

Built by marketers who've carried the number, and engineers from the search and recommendation teams that decide which brand gets named.

Ex-FAANG engineering Search & recommendation Brand & growth leadership Billions of queries shipped
01

We've sat in your seat

Marketers who briefed the agencies, carried the pipeline number and defended the brand budget.

02

We built the engines

Engineers from FAANG-scale search and recommendation teams — the systems that now choose which brand gets named.

03

We obsess over the answer

We reverse-engineer how models weigh sources, so your place in the answer is earned by design.

09 / The brief

Machine Readable

A weekly brief on what AI is saying about brands — and what to do about it. Five minutes, every Tuesday.

Free · On Substack · No fluff · Unsubscribe anytime
You're in. First issue lands Tuesday.
Beyond SEO · Beyond search · Beyond opinion

Own
the answer

See what AI tells your buyers about your brand. A 30-minute walkthrough — your category already scanned.