AI Visibility & AEO Platform for Brands | AnswerTrace
Built for Indian brands · All Indian languages

Get your brand recommended
in AI answers.

Indian buyers ask ChatGPT, Perplexity, and Google AI which brand to use, in English, Hindi, Hinglish, Tamil, Telugu, and more. The next step is AI agents that research and buy on their behalf. AnswerTrace is the software that measures where you're named across all Indian languages, shows you why you lose, surfaces exactly what to fix, and reports on what changed, from AI query to revenue.

See where you're not being recommended Free scan · No credit card · Tracks all Indian languages
Measured across
ChatGPT
Google AI
Perplexity
Claude
The problem

Indian buyers use AI to shortlist. Most Indian brands lose before the conversation starts.

When an Indian buyer asks ChatGPT which SaaS tool, fintech platform, or D2C brand to use - in English, Hindi, Hinglish, Tamil, or Telugu - they get a short answer naming one or two options. The brands named start the sales conversation. The rest are never considered. And most Indian teams have no idea which side they're on, or why.

180M+
weekly users in India turning to AI for product recommendations
AI-assisted shortlisting is now standard across Indian fintech, SaaS, D2C, and consumer categories - in English, Hindi, Hinglish, Tamil, Telugu, and more. Buyers ask, they get a name, they start evaluating. If that name isn't yours, you never entered the funnel.
1-2
brands get named per recommendation - not ten
AI answers are not ranked lists. They are recommendations. The winner-takes-most dynamic is far more pronounced than in search - and Indian brands are losing ground to global competitors who appear first in AI answers.
0
India-built platforms tracking all Indian language AI visibility - until now
Global AEO tools are English-only. A buyer asking "best payment gateway India mein" or "சிறந்த CRM எது" gets a completely different AI answer - and no one was measuring that gap for Indian brands. Until now.

The harder problem is not just appearing - it is being chosen. Many brands now appear occasionally in AI answers but are not consistently recommended. Appearing once does not win the shortlist. Consistent recommendation does. Most teams don't know which side they are on, and don't know why they lose when they do. The reasons are specific and fixable.

What we measure

AI recommendations influence every stage of the buying decision.

AnswerTrace tracks your recommendation rate across the full buyer funnel - from first awareness through final decision - so you know exactly where you win, where you lose, and what the gap costs.

DISCOVERY "What are the best tools for X?" Are you named when buyers first map the category? CONSIDERATION "Is [brand] good for my use case?" Are they recommended for the problems they solve? DECISION [Brand A] vs [Brand B] which is better? TRUST Is [brand] reliable and worth it? ✓ The Chosen Brand
A concrete example

This is what your buyers actually see.

A buyer asks ChatGPT for a recommendation. The AI responds. Two brands get named. Yours isn't one of them - and you don't know why.

Buyer query to ChatGPT
"Best CRM for a growing business"
ChatGPT's response
For a growing business, I'd usually recommend HubSpot for ease of use and fast onboarding, or Salesforce if you need deeper customization and enterprise workflows. If you want a strong value option, Zoho CRM is also frequently considered...
YourBrand - not mentioned. This query ran across 4 engines, 8 responses. Your brand appeared 0 times. HubSpot, Salesforce, and Zoho CRM dominated the answers.
What AnswerTrace diagnoses
No FAQ or comparison content on your site targeting "best CRM for a growing business" - AI engines have nothing clear to cite.
Competitors have 4-6x more editorial mentions on G2, ProductHunt, and third-party roundups AI treats as source material.
Your homepage lacks structured schema - crawlers can't parse what you do, who you serve, or what category you're in.
Your competitors are featured in 12+ recent roundups on sources AI engines pull from. You aren't in any of them.

This is a representative example. Your actual scan shows real responses, real gaps, and specific fixes, for your brand and category.

The platform

Four steps. One flywheel: be the brand AI recommends.

1
Measure
Know exactly where you stand
AnswerTrace runs the buyer queries that matter across ChatGPT, Google AI, Perplexity, and Claude, giving you a recommendation rate by engine, query type, and funnel stage. Not a vanity score.
2
Diagnose
Know exactly why you lose
AnswerTrace traces which signals your competitors have that you don't: missing content, citation gaps, schema deficiencies, entity inconsistency. You see the cause, not just the gap.
3
Act
Act from the platform. Not from a to-do list.
Apply fixes without leaving AnswerTrace. Publish buyer-question content, schema updates, and entity alignment to WordPress and your CMS in one click. Citation gaps surface as a prioritized list for your team to action. Automation optional.
4
Attribute
See what changed and why
AnswerTrace re-runs the same queries and reports rate changes mapped to the specific fixes your team shipped, by engine, query type, and funnel stage. AI-referred sessions are reported through to conversions and revenue. AI query, to recommendation, to visit, to signup, to sale.
↩ loops back to Measure. Recommendation rate compounds into revenue.
Product tour

See the platform in action.

AnswerTrace running on Nexus, a fictional B2B SaaS brand. Watch the walkthrough below.

app.answertrace.com/nexus-demo
tour
Measure your AI visibility →
Every loop, your recommendation rate compounds into revenue.
Measure → Diagnose → Act → Attribute → back to Measure
01 · MEASURE Measure Recommendation rate by engine, query type, and funnel stage. not a vanity score. 02 · DIAGNOSE Diagnose Trace which signals competitors have that you don't: content, citations, schema, entity. 04 · ATTRIBUTE Attribute Map rate changes to specific actions, and trace sessions to conversions and revenue. 03 · ACT Act Push fixes to your CMS. Content, schema, citations. One click. Automation optional. ↻ Recommendation → Revenue BUSINESS OUTCOME AI → Revenue
01 · MEASURE
Measure
Recommendation rate by engine, query type, and funnel stage. Not a vanity score.
↓
02 · DIAGNOSE
Diagnose
Trace which signals competitors have that you don't: content, citations, schema, entity.
↓
03 · ACT
Act
Push fixes to your CMS, one click. Content, schema, citations. WordPress and major CMS integrations built in. Automation optional.
↓
04 · ATTRIBUTE
Attribute
Map rate changes to specific actions, and trace sessions to conversions and revenue.
↻ Recommendation → Revenue
How it works

Measure. Diagnose. Act. Attribute.

AnswerTrace runs the full loop, from baseline measurement through the work your team ships to outcome reporting. Not a monitoring feed. Not a backlog you have to action in a separate tool. Apply fixes directly from the platform, one click to your CMS, and see exactly what moved.

1
Measure
Map and run the buyer queries that actually matter
AnswerTrace identifies the prompts buyers in your category are using, from early discovery through evaluation and validation, then runs them across ChatGPT, Google AI, Perplexity, and Claude and measures your recommendation rate on each one.
2
Diagnose
Identify exactly why you're losing - and to whom
Not just a score. AnswerTrace traces the specific signals your competitors have that you don't: missing content types, citation gaps on sources AI engines trust, schema deficiencies, entity inconsistency. You see the cause, not just the symptom.
3
Act
Apply the highest-impact fixes, directly from the platform
AnswerTrace surfaces exactly what to fix: buyer-question content, schema updates, entity clarity, third-party citation and review gaps. Your team publishes from the platform in one click. Direct integrations with WordPress and major CMS platforms. Start with one-click publishing; automation scales with you.
4
Attribute
Attribute to actions and trace through to revenue
After your team ships fixes, AnswerTrace re-runs the same queries and compares recommendation rates before and after, by engine, query type, and funnel stage. The platform maps improvement to the specific actions you took, and reports AI-referred sessions all the way through to conversions and revenue. AI query, to recommendation, to visit, to signup, to sale.
What the platform surfaces

Specific actions, not generic advice.

AnswerTrace surfaces the highest-leverage fixes first, the actions with the clearest path to increasing your recommendation rate across the engines and query types that matter most for your category, so your team works on what moves the needle.

✍️
Buyer-question content
FAQ pages, comparison content, use-case pages, and category definitions written to match the exact queries AI engines pull from - in your category, for your audience.
🏗️
Schema and entity definitions
Structured data that makes your category, audience, product, and value proposition explicit and machine-readable - so models can represent you accurately and confidently.
📣
Third-party citation gap analysis
A prioritized list of the review platforms, editorial roundups, marketplace profiles, and community sources that AI engines weight most heavily in your category, where your brand is currently missing. Your team or PR partner closes each one.
🔄
Entity and positioning consistency
AI systems construct your brand's identity from signals across your site, third-party profiles, and editorial sources. AnswerTrace defines the machine-readable version: category, audience, value proposition, and structured attributes, then aligns it across every surface AI engines index. Think of it as your brand's permanent record in the AI layer.
🇮🇳
All Indian language visibility
Indian buyers ask AI questions in English, Hinglish, and regional languages, and get completely different answers. A fintech brand dominant in English queries may be invisible when someone asks "best payment app India mein" or "kaun sa CRM acha hai startups ke liye." AnswerTrace tracks your visibility across all three: English, Hinglish, and Hindi, with Tamil, Telugu, and Kannada support coming next. Your team gets the same prioritized fix list for every language.
Attribution

Know what changed and why, not just that something did.

Most platforms tell you your mention count went up. AnswerTrace tells you which specific fixes your team shipped caused the increase, on which queries, and on which engines. That reporting is what lets you compound the right work instead of repeating everything.

Before
Recommendation rate: 12% across 40 tracked queries. Losing on all comparison and use-case queries. Named on 2 of 10 discovery queries on Perplexity, 0 on ChatGPT.
Shipped
The platform surfaced 6 high-impact fixes. The brand's team published buyer-question content pages, schema updates, and entity definitions to their CMS using AnswerTrace's one-click publish. AnswerTrace also listed 4 third-party citation gaps for the team to close on their own.
After
Recommendation rate: 41% across same 40 queries. Named on 7 of 10 discovery queries. Winning 4 of 6 comparison queries where previously absent. Each rate change reported against the specific content asset or citation source the team shipped, with AI-referred sessions reported through to 12 converted signups.

Where AI engines identify the referring session, AnswerTrace reports it directly against conversions and revenue. Where they don't, the platform correlates recommendation rate changes with pipeline movement over the same period. Both signals are reported separately, so you always know which is a direct measurement and which is a correlation.

What makes this different

Other platforms track mentions.
AnswerTrace runs the full AEO loop.

Monitoring what AI says about you is the start. Knowing why you lose, having the fixes ready to ship, and reporting on what changed is how you win. See how AEO differs from SEO.

Monitoring tools
AnswerTrace
Show you a mention count or visibility score
Show recommendation rate by query type, engine, and funnel stage
Tell you competitors are winning
Show you which competitors, on which queries, and what signals they have that you don't
Give you a backlog of recommendations
Surface the highest-impact fixes so your team can ship them in one click, CMS integrations built in, automation optional
Track changes over time without explaining them
Report rate changes against the specific fixes your team shipped, with AI-referred sessions reported through to conversions and revenue
Require ongoing setup and dashboard interpretation
Run the loop end to end: measure, diagnose, act, attribute
Who it's for

Built for the brands AI is already judging.

The AI recommendation gap shows up differently depending on your category. Here's how AnswerTrace applies to yours.

⚙️
B2B SaaS
Win the AI shortlist before buyers reach your pricing page.
B2B buyers use ChatGPT and Perplexity to shortlist software before they visit a single website. If you're not named in those answers, you never enter the evaluation. AnswerTrace measures your recommendation rate across buyer queries, from discovery through comparison, and surfaces the fixes your team should ship to get named consistently.
B2B SaaS visibility
🛍️
D2C & Ecommerce
Get named when shoppers ask AI which brand to buy.
Shoppers ask AI "best skincare brand for oily skin" or "top D2C protein brand India mein", in English, Hinglish, and regional languages. The brand AI names first wins the consideration. AnswerTrace tracks where your brand appears across those queries and reports AI-referred sessions all the way through to purchases.
D2C & ecommerce visibility
🏢
Agencies
AEO software for agency teams. Run the loop across every client.
AEO is the next capability clients will expect, the same inflection SEO had ten years ago. AnswerTrace is the AEO software agency teams standardize on, so one team can measure, prioritize, and report on AI visibility across every client account.
AEO for agencies
Common questions

Everything you need to know.

AEO, SEO, why you're losing, and how AnswerTrace works.

Yes, that's a core part of what makes AnswerTrace India-first. The platform tracks buyer queries across all major Indian languages: English, Hindi, Hinglish, Tamil, Telugu, Kannada, Marathi, and more. The competitive landscape shifts completely by language: a brand dominant in English AI answers can be invisible when a Tamil or Telugu buyer asks the same question. AnswerTrace runs prompts like "best CRM for Indian startups", "kaun sa payment gateway sahi hai", "சிறந்த HR software எது", and "best fintech app India mein", and shows you your recommendation rate per language so you know exactly where your gaps are.
It's built for exactly these categories. Indian SaaS brands face a specific challenge: AI engines often recommend global competitors (Salesforce, HubSpot, Stripe) even when the buyer is asking specifically about the Indian market. AnswerTrace tracks "Indian alternative to X" queries, comparison prompts ("Razorpay vs PayU"), and trust queries ("is [brand] RBI compliant"), the exact prompts where Indian brands lose. For D2C, the platform tracks discovery queries in vernacular languages where your brand may be invisible. For fintech, it tracks the compliance and trust signals AI engines weight most heavily in the Indian context.
AEO (Answer Engine Optimization) is the practice of ensuring your brand gets named when AI engines answer questions your buyers are asking. SEO gets you ranked in a list of ten blue links. AEO gets you named as the recommendation. The signals are different: SEO rewards backlink volume, keyword density, and page authority. AEO rewards direct Q&A content, editorial citations, entity clarity, and structured data. You can rank #1 on Google and be completely invisible on ChatGPT. And increasingly, buyers encounter the AI answer before they ever scroll to organic results.
Yes. SEO and AEO are complementary, not competing. Strong SEO authority (domain trust, backlinks, indexed content) feeds AI engines. They use web-indexed content as source material. The shift is that SEO alone no longer guarantees discovery. Brands that invest in both build a compounding advantage: strong SEO gives AI engines more to cite; strong AEO makes sure they actually do.
The most common reasons: (1) Missing buyer-question content: your site doesn't directly answer the questions AI pulls from, so there's nothing to cite. (2) Thin third-party coverage: competitors appear in more G2, Capterra, TechCrunch, and roundup mentions that AI engines weight heavily. (3) No schema markup: crawlers can't easily parse what you do, who you serve, or what category you're in. (4) Weak entity consistency: your brand description varies across your site and off-site profiles, making it harder for AI to recommend you confidently.
Most SEO tools adding AEO are doing monitoring only: they show you a mention count or score and stop there. You still have to figure out why you're losing, what to fix, and how to do it. AnswerTrace runs the full loop: measure, diagnose, apply fixes directly from the platform, and report what changed back to specific actions, all the way to revenue. That end-to-end workflow and reporting layer is what no monitoring-first tool has. The deeper difference is architecture: AEO is being bolted onto SEO tools. AnswerTrace was built from the ground up for AI recommendation.
You can ask ChatGPT about your brand, but that's one query, one engine, one moment in time. AnswerTrace runs hundreds of buyer queries across four engines, segmented by funnel stage and query type, and tracks changes over time. It diagnoses why you're losing and maps specific fixes to specific results. Manually checking ChatGPT is like checking your site traffic by visiting it yourself.
Measurement is immediate: your baseline recommendation rate is ready from your first scan. Improvement typically shows in 4 to 8 weeks as your team publishes content and citation fixes and AI engines re-crawl. Clear reporting, knowing exactly which actions your team took moved which queries, becomes visible after the first full loop, usually 6 to 10 weeks in.
Yes, your foundation isn't wasted. Strong content, high-authority backlinks, and a well-indexed site all feed AI engines. What AnswerTrace adds is the layer on top: making sure that content is structured in ways AI can cite, that you appear in the third-party sources AI trusts, and that your brand is defined consistently enough for AI to recommend you confidently. You start with an advantage over brands starting from zero.
ChatGPT, Google AI Overviews, Perplexity, and Claude. These four account for the large majority of AI-assisted product research today. Each weights signals differently. A brand can dominate on Perplexity and be invisible on ChatGPT. We break down recommendation rate per engine so you know exactly where your gaps are most severe and which fixes move which engine.
Get started

Be the brand AI recommends.
Trace it all the way to revenue.

AnswerTrace measures your recommendation rate across ChatGPT, Google AI, Perplexity, and Claude, shows you exactly where you're losing and why, lets your team apply fixes directly from the platform, and reports what changed all the way to revenue.

Recommendation rate measurement
Competitor gap diagnosis
Score ready in minutes
1
Enter your
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2
Scans 4 AI
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See where you're not being recommended
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