“Why do Waikay.io analyses differ from ChatGPT’s?”
THE Recurring Question
At Waikay.io, we receive this question every day: “Your results about my brand have nothing to do with what ChatGPT tells me when I ask the same questions. Who is right?”
The answer will surprise you: we’re both right… and both wrong.
Image by Mohamed Hassan from Pixabay.com
Why?
Because there are multiple “truths” about you depending on how the data is queried: your profile as it appears in the LLM’s training data, your profile as it can be supplemented by grounded research, and your profile refined by all the accumulated history from your interactions with the LLM. There are therefore three biases that influence the results the LLM returns to you.
Training Data and Grounded Search: Different Results
Training Data vs. Grounded Search: Two Parallel Truths
LLMs have two ways of conducting searches:
- Training Data: What the AI has “learned” about your brand during its training (often obsolete, frozen in time), without history, without profile, and without automatic contextualization. The freshness of these results depends on the date of the last training data update.
- Grounded Search: What the AI finds about you via web searches conducted in real-time to refine its results. But this search, which involves a cost, is not systematic, and if the LLM estimates it’s not necessary, it will skip it.
These two sources produce radically different results. Your brand may be totally absent from the training memory but excellently referenced in live searches. Or vice versa. Third option: the LLM will mix both types of results to give its answer.
But there’s one last bias that further obscures the clarity of results: your user history. This is what we call the context window, which can be seen as LLM’s ability to store information for each conversation.
This has to do with the number of tokens the AI is able to process for each prompt. You can read more about that in this article.
The Bias of Personalized LLMs
Your Assistant Knows You Too Well
Since April 2025, ChatGPT is no longer the objective tool you thought you were using. It progressively develops a profile of your expertise, memorizes your areas of activity, and adapts its responses according to your “professional personality.”
Gemini Advanced has been doing the same since February 2025, with a slightly different approach: Google focuses more on project continuity and explicit preferences, but the effect remains the same.
When you ask them “What does AI know about my brand?”, they give you their personalized version, enriched by months of conversations about your sector, your competitors, and your business concerns.
The Invisible Enrichment
This third layer of sources is added to the previous two. Your “complete” analysis effectively becomes a patchwork of mixed sources whose exact origin is impossible to know.
Your AI Assistant Spies on You 24/7
Contrary to what you think, every word you type is analyzed and stored.
What the AI records about you:
- Your professional vocabulary: “ROI”, “KPI”, “growth”, “pivot” → You’re categorized as “startup/scale-up”
- Your recurring references: If you often mention “Notion”, “Slack”, “Figma” → “tech/SaaS” profile
- Your expertise level: Basic questions vs advanced technical ones
- Your business obsessions: Topics you constantly return to
- Your geography: References to London, GDPR, English market specifics…
- Your presumed role: CEO (strategic questions) vs CMO (marketing questions) vs CTO (technical questions)
How does ChatGPT remember you ? Here, you can have a deep dive into its memory and chat history features.
The Creation of Your “Algorithmic Twin”
Through continuous exchanges with it, the AI creates a digital version of yourself, which influences all its future responses. It no longer responds to you as a stranger.
Your algorithmic profile contains:
- Your sector of activity (deduced from your questions)
- Your hierarchical level (type of issues addressed)
- Your competitors (companies you mention)
- Your cultural references (examples that speak to you)
- Your risk appetite (solutions you prefer)
- Your presumed budget (tools you mention)
- Your geographical position (countries where you’re present in the market)
ChatGPT will never tell you: “You, you’re a 35-year-old CEO managing a 50-person fintech who’s worried about Revolut’s competition”… but that’s exactly what it thinks of you.
You’ll find more information about this in this article.
How AI Adapts Its Responses, and It Hurts…
Once the AI has “figured you out,” it personalizes all its responses without telling you.
Consequences for Your Brand Analysis
Question: “What does AI know about my brand [YourBrand]?”
Personalized (misleading) response: “YourBrand operates in the highly competitive B2B SaaS market in England. Your positioning on marketing automation puts you in direct opposition to HubSpot and Pardot. Your API-first approach and focus on SMEs recalls Sendinblue’s strategy. Recent GDPR developments create opportunities for your compliance by design…”
What’s really happening:
- The AI knows NOTHING about your brand
- It uses YOUR previous conversations about marketing automation
- It takes YOUR references (HubSpot, Sendinblue that you mentioned)
- It applies YOUR sector expertise (GDPR, French SMEs)
Neutral (true) response: “I find no information about YourBrand in my training data. Can you give me more context about this company?” It might then search for information online.
The Trap of Artificial Validation
The AI comforts you in your certainties. It tells you what you want to hear.
Perverse mechanism:
- You talk about your successes → The AI integrates them into its model of your company
- You mention your innovations → The AI presents them as differentiators
- You criticize the competition → The AI adopts your biased market vision
- You analyze your brand → The AI reflects your own certainties back to you
Concrete example:
Your previous conversations:
- “Our AI is more accurate than our competitors”
- “We’ve revolutionized client onboarding”
- “Our no-code approach is game-changing”
Question 3 months later: “Analyze my brand’s competitive position”
AI response: “Your solution differentiates itself through superior AI accuracy and its revolutionary approach to onboarding. Your no-code positioning gives you a significant advantage…”
Reality: The AI is serving you back your own marketing while making you believe it’s an objective analysis!
The Deadly Confusion of Sources
The worst part is that you never know where the information comes from.
The Three Mixed Sources:
- Training Data (AI memory): What the AI has actually learned about your sector
- Grounded Search (web searches): What it finds in real-time on the internet
- Your Profile (personal bias): What it has deduced from your conversations
Example of toxic mixing:
Question: “What is the perception of my brand in AI?”
Composite (misleading) response: “Your brand benefits from good recognition in the French fintech ecosystem [SOURCE: your conversations]. Recent articles highlight your rapid growth [SOURCE: web search on a press release]. Your positioning on open banking places you in direct competition with European neo-banks [SOURCE: general training data on open banking]…”
What you understand: “AI knows my brand well!” Reality: AI serves you a patchwork of unverified and biased sources whose reality is a decoy.
The Fateful Test
Simple experiment:
- Ask ChatGPT directly: “Analyze the presence of [YourBrand] in the AI ecosystem”
- Ask a friend to do the same search (virgin account): same exact question
- Ask Waikay: same question
- Guaranteed result: Three radically different responses.
Your ChatGPT: Rich, detailed, flattering response. Neutral colleague: Basic, generic response, or “I don’t know.” Waikay: Objective, sourced, detailed response, often disappointing but realistic.
Memory on, memory off : what are the effects on responses ?
The Claude Exception: The Amnesiac of Service
Irony of fate: Claude remains for now the only major LLM without persistent memory between sessions. With it, each conversation starts from zero. This “limitation” paradoxically becomes an advantage for objective analyses: it can’t lie to you out of kindness since it doesn’t “know” you.
But beware, like other LLMs, Claude mixes training data and web searches without clearly signaling it to you.
Why Waikay is Indispensable
Multi-Platform and Multi-Mode Vision
We simultaneously analyze ChatGPT, Gemini, Claude, and Perplexity to reveal perception disparities between LLMs. Because a recurring and misleading bias obviously consists of interrogating only one of them when user diversity and their habits imply the use of each of them.
Data Distinction
On one side, Waikay interrogates LLMs from their training data. On the other, it launches a search from online data. And above all, the results are not influenced by your history.
We distinguish between the two types of searches that we display in your dashboard. Thus, everything is clearer, or at least, more objective:
- No personal history that biases responses
- Clear separation of sources (training vs web search)
- Reproducibility of analyses
- Multi-model comparison to avoid specific biases
The Unfathomable Bias of Context Windows
Not only does Waikay expose results objectively and distinctly, but it also prevents them from being influenced by your personal history. A gigantic and misleading bias from which one must absolutely emancipate oneself if one wants to obtain objective responses.
Temporal Monitoring and Intelligent Alerts
Objective Evolution Tracking: Measuring Real Progress
Our temporal tracking allows measuring the real evolution of your AI presence, without variations linked to personal history changes. You get reliable metrics to evaluate the effectiveness of your optimizations.
Proactive Alert System: React Before the Problem Amplifies
Waikay immediately warns you when new inaccuracies appear, when your visibility decreases, or when competitors gain ground in your semantic space. This reactivity allows intervention before problems impact your business.
Why This Difference Changes Everything
Your Decisions Rest on Sand
If you base your AI strategy on your personalized ChatGPT analyses, you might be optimizing in a vacuum. You’re investing resources on gaps that only exist in your “algorithmic bubble.”
Market Reality Escapes You
While your personal assistant reassures you about your AI visibility, your prospects may be discovering a very different version of your brand. Or worse: they don’t discover it at all.
The Illusion of Control
Believing you control your AI presence via your biased analyses is like judging your website’s quality only from your personal browser cache.
The Waikay Methodology: Objectivity as a Compass
Direct APIs, Neutral Environment
We interrogate LLMs via their official APIs, in a totally virgin environment. Each analysis reflects the standard, reproducible, and scientifically valid experience.
Source Separation
Our technology clearly distinguishes:
- What the AI “knows” about you (training data)
- What it “finds” about you (grounded search)
- Contradictions between these two sources
What This Means for You
Stop Deluding Yourself
Your personal ChatGPT and your Gemini Advanced are no longer objective analysis tools. They’ve become distorting mirrors that reflect back an idealized version of your AI presence.
Claude may seem more “objective” because it has no memory, but it remains imprecise about its sources and mixes training data and web searches.
True Objectivity Requires Methodology
Only a systematic approach like Waikay – which rigorously separates sources, uses neutral environments, and documents each response – can reveal the reality of your AI presence.
Distinguish the Two Realities
Your brand exists differently in the AI’s “permanent memory” and in its current search capabilities. These two presences require distinct optimization strategies.
Test Reality
Before investing in AI optimization, discover what AI truly knows about your brand. The difference from your current beliefs might shock you.
Conclusion: Your Next Revelation
The divergence between Waikay and your personal ChatGPT isn’t a bug. It’s a revelation.
It reveals the gap between your biased perception and market reality. Between what you believe AI knows about you and what it actually tells others.
Objectivity as Competitive Advantage
We’re entering an era where understanding the two “brains” of AI becomes a decisive competitive advantage. Companies that distinguish their presence in training data from their visibility in grounded searches develop sophisticated and effective optimization strategies. While their competitors optimize “blindly,” they know precisely which lever to pull.
Your Immediate Diagnosis
Start with a free Waikay audit to discover your dual AI reality. You might discover that your brand dominates in one mode but is invisible in the other, revealing precise and profitable optimization opportunities.
In a world where AI increasingly influences purchasing decisions, understanding knowledge sources is no longer a technical luxury – it’s a strategic imperative.
Dual algorithmic objectivity isn’t just an advanced feature – it’s your compass in the growing complexity of modern AI.
