You become a generic version of yourself.
AI flattens a differentiated product into a broad category buyers already understand, then compares you on the wrong criteria.
Result: value disappears.AI Buyer Intelligence for B2B SaaS
AI can remove you from the shortlist before sales sees the deal.
Before a prospect books a demo, AI may already have recommended a competitor, questioned your enterprise readiness, or framed your company through outdated evidence.
In 20 minutes, Memetic Intel shows you what ChatGPT, Claude, Gemini, and Perplexity say about your company, what is driving the answers, and what to fix first.
20 minutes/Your company/Answers verbatim/No prep
01 · Not shortlisted
AI recommends better-known vendors first.
Your company never reaches the evaluation.
02 · Trust questioned
Missing proof reads as immaturity.
Security, scale, and customer evidence remain invisible.
03 · Incumbent wins
The safer-looking competitor gets the call.
Public evidence beats private capability.
01Buyer Research Console
See the judgment. Trace the evidence. Find the commercial risk.
This illustrative console mirrors the working session: a buyer question, the answer pattern across major models, the evidence behind it, and the consequence for the deal.
ChatGPT · illustrative buyer research session
Buyer prompt
“Which vendors should we shortlist for an enterprise rollout, and what are the risks?”
Answer pattern
The company appears credible on core capability, but public evidence of enterprise scale is limited. Buyers may prefer two better-known alternatives with clearer deployment proof.
Commercial consequenceSafer competitor recommended before first contact
Evidence trace
Hover to connectCapability is visible. Enterprise certainty is not.
Illustrative answer patterns, not client results. The live Walkthrough runs real prompts on your company and shows outputs verbatim.
01Buyer asks AI
02Public evidence is synthesized
03Shortlist and objections form
04Sales sees only the survivors
Your CRM records the call. It does not record the buyers AI removed before it.
02Where deals break
Four ways the public record quietly works against the sale.
The proof your sales team uses is invisible.
Security, deployment, and customer evidence is gated, buried, unnamed, or too fragmented to support confidence.
Result: “promising but early.”The incumbent gets the benefit of the doubt.
Better-known vendors have clearer comparison pages, more citable evidence, and stronger third-party narratives.
Result: safer alternative recommended.Your old company story still defines you.
A funding announcement, old positioning, or outdated category label remains the easiest canonical description to find.
Result: current strength is ignored.AEO asks
“Do we appear?”
→
AI Buyer Intelligence asks
“When we appear, does the answer help us win or quietly remove us from consideration?”
What AI may see now
- Gated compliance PDF
- Old funding announcement
- Generic homepage claims
- Unnamed enterprise customers
- Competitor-authored comparison
What the public record may need
- Accessible trust and security page
- Current canonical company description
- Citable enterprise proof
- Clear category and use-case language
- Evidence-led competitive pages
The objective is not to manipulate a model. It is to make the strongest true version of the company easier to verify.
03The 20-minute Walkthrough
A working diagnostic, not a discovery call.
You see the actual buyer-facing answers, the first evidence gaps, and whether deeper work is warranted. You keep the outputs either way.
0–3 min
Frame the buyer
Your company, target buyer, category, and one meaningful competitor.
3–15 min
Run the evaluation
Shortlist, comparison, enterprise readiness, trust, and risk prompts across major AI systems.
15–20 min
Diagnose the first gaps
What is helping, what is missing, and the first one to three issues worth investigating.
Low-friction by design
You leave with something concrete.
- No preparation required
- No sensitive internal data
- Real prompts run live
- Answers shown verbatim
- Outputs are yours to keep
04Flagship finding
A real commercial problem can look like “promising but early.”
Composite example
“Can this company support enterprise deployment in regulated industries?”
AI repeatedly recommends a pilot and routes enterprise buyers toward two incumbents with clearer public trust evidence.
Hidden lossThe buyer chooses the safer incumbent before your team knows an evaluation happened.
Likely cause
SOC 2 exists, but no public trust page explains it. Enterprise wins are real, but unnamed. A 2022 funding story remains the most-cited company description.
First move
View four more finding patterns →
Publish accessible security and deployment proof, then replace the stale company narrative with a current canonical description.
05The paid engagement
The Sprint turns the diagnostic into a decision-ready evidence agenda.
Three weeks. A defined question set. An executive briefing that shows where AI helps or hurts, why, and which pages and proof assets should change first.
Buyer Question Map
The shortlist, trust, risk, category, pricing, and comparison questions tested across systems.
Answer & Evidence Trace
Cross-model answer patterns mapped to the public record likely producing them.
Priority Evidence Agenda
The pages, claims, and proof assets leadership should change first.
Retest Baseline
The original questions and outputs preserved so changes can be evaluated.
Founder-led by Marc Osborn
Every Walkthrough and Sprint is led by the person responsible for the diagnosis.
Memetic Intel combines AI systems testing, competitive intelligence, positioning analysis, and buyer-trust research. The value is senior judgment and executive translation, not dashboard volume.
How the practice works →
You should see this now if
- Buyers compare you against larger incumbents
- Your enterprise proof is stronger than your website suggests
- Your category or positioning changed recently
- Sales encounters unexplained trust objections
- One lost shortlist is worth materially more than the diagnostic
06See the hidden layer
Find out whether AI is helping you win, or quietly removing you from consideration.
See whether there is a real problem before funding a larger initiative.