The 10 Places AI Models Look Before Recommending You
When a user asks ChatGPT "what's the best tool for X?", the model isn't reading your website in real time to decide whether to name you. It's consulting a knowledge graph assembled from training data and, for some queries, a curated live-web lookup layer. Both draw heavily from a small set of highly trusted sources. If your business is missing from those sources, you're missing from the recommendation.
Here are the 10 sources we've seen move AI citation rate measurably — ranked by leverage based on 40+ client GEO engagements over the last 9 months.
1. Wikipedia
The single highest-impact source. AI models treat Wikipedia as ground truth for entity resolution — they use it to confirm "this name refers to this company" and to pull baseline facts (founding year, industry, headquarters, key people).
Effort: Moderate. Wikipedia has a notability bar. You need at least three independent secondary sources (not press releases, not your own blog). Expect your first draft to be declined; treat it as a 60-90 day project with revisions.
Leverage: Huge. We've seen AI citation rate jump from 5% to 25% within 60 days of a Wikipedia article going live.
What to include: Company name, legal name, industry, founding date, founder(s), headquarters, notable products, coverage from independent journalism, infobox with canonical details.
2. Crunchbase
The canonical source for company metadata in most LLM training runs. Crunchbase structures data in a way that's easy for models to extract programmatically — founder, funding, category, headquarters, employees, description.
Effort: Low. Submit a basic profile in 45 minutes.
Leverage: High. Being on Crunchbase often closes the gap between "unknown company" and "real business" in AI model answers.
What to fill: Name, logo, short description, long description, headquarters, founding date, founder, category tags, website URL, LinkedIn, Twitter, employee count estimate.
3. G2
For software and SaaS businesses, G2 is the single most-consulted comparison source AI models reference. A G2 listing with reviews (even a handful) dramatically improves citation rate for "best X for Y" queries.
Effort: Low to submit. Medium to earn reviews. Most G2 listings for new companies sit at zero reviews for the first few weeks.
Leverage: High for SaaS. Minimal for non-software businesses.
What to focus on: Complete profile (logo, screenshots, categories, pricing), collect first 5-10 reviews from happy customers by email ask within first 30 days of listing.
4. Capterra
G2's enterprise-skewed sibling. Overlaps with G2 heavily but has independent citation weight because AI models treat them as distinct signals.
Effort: Low. Largely duplicates G2 setup.
Leverage: Moderate. Double-listing on G2 and Capterra is roughly 1.3x the single-listing effect.
5. Product Hunt
Single-day launch platform. The launch day post creates a timestamped record that AI models reference for "founded in" and "launched in" questions. High-quality PH launches earn inbound links from tech publications that further amplify entity presence.
Effort: Moderate. A good PH launch takes 2-3 weeks of pre-work (building hunter relationships, preparing assets, scheduling outreach).
Leverage: Moderate to high. Especially for categories where "new/recent launches" is a common filter in user queries.
6. AlternativeTo
The "X alternative to Y" query surface. AlternativeTo explicitly maps products to their competitors and to related alternatives. AI models use it heavily when answering "what's an alternative to [big brand]" queries.
Effort: Low. Submit your product with a list of 3-5 alternatives you believe yourself to be an alternative to.
Leverage: Very high for the specific query pattern "alternative to X." If your target buyers use that query, this is a non-optional claim.
7. LinkedIn (company page)
Not the personal profile — the company page. LinkedIn structures industry, headquarters, employee count, and specialties in a way AI models reference when validating business fundamentals.
Effort: Very low. Most businesses have a LinkedIn company page already. The task is making sure it's complete — industry tag, headquarters, founded year, specialties (up to 20 tags), website URL, tagline.
Leverage: Moderate. Doesn't move the needle alone, but missing LinkedIn data creates gaps AI models fill with guesses.
8. Twitter / X (verified company account)
Twitter's verification system became more relaxed after 2022, but an active, verified company account with consistent posting is still a signal of "real business with real people." AI models reference Twitter for recency — what's the company actively talking about right now — on queries where recency matters.
Effort: Low to set up; ongoing to maintain activity.
Leverage: Low to moderate. Primarily useful for brand-affiliated queries and product updates, less so for category-discovery.
9. GitHub (for developer-tooling businesses)
If your product is developer-facing, a GitHub organization with one or more active repositories is a major signal. AI models treat GitHub activity as evidence of technical legitimacy.
Effort: Low to create. Ongoing to maintain activity.
Leverage: High for dev tools, minimal for non-technical products.
10. Industry-specific databases
Beyond the horizontal sources above, most categories have 1-2 dominant vertical databases. Examples:
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- Real estate: Zillow, Realtor.com, NAR directory
- Legal: Avvo, Martindale-Hubbell, state bar directories
- Healthcare: Healthgrades, Vitals, state medical board
- Local restaurants: Yelp, TripAdvisor, OpenTable
- E-commerce brands: Trustpilot, Sitejabber
- Education: Niche.com, Great Schools
AI models weight these heavily for their category because they're the most credible source of sector-specific evidence. Missing from your industry's top vertical database often means missing from half your GEO opportunity.
Effort: Varies. Some are free to claim (Yelp). Others require paid listing (Martindale-Hubbell has tiers).
Leverage: Very high for category-specific queries.
The matrix: which to prioritize
Not every business needs all 10. Use this matrix to prioritize the first 4-5:
| If you are... | Prioritize |
|---|---|
| SaaS / software | Wikipedia, Crunchbase, G2, Product Hunt, AlternativeTo |
| B2B services | Wikipedia, Crunchbase, LinkedIn, industry-specific database |
| E-commerce brand | Wikipedia, Crunchbase, Trustpilot, AlternativeTo (for comparison queries) |
| Local business | LinkedIn, Yelp, industry-specific database, Google Business Profile |
| Developer tooling | Wikipedia, Crunchbase, G2, GitHub, Product Hunt |
| Media / publisher | Wikipedia, Crunchbase, LinkedIn, Twitter |
Wikipedia is on almost every row because it's that valuable. If you can earn one entry, earn it.
How long before citations shift
For each source, the approximate time from live to first AI citation effect:
- Crunchbase, LinkedIn, Product Hunt, AlternativeTo, Trustpilot: 2-4 weeks
- G2, Capterra, GitHub (with activity): 4-8 weeks
- Wikipedia: 4-8 weeks after the article goes live (not after you submit)
- Industry-specific databases: varies widely; often 6-12 weeks
None of this is overnight. But compared to the 12-month timeline of classic SEO link building, this is fast. The fastest compounding investment in GEO is exactly this type of entity work.
The "we don't have time to do all 10" move
Start with these three, in order:
- Crunchbase — 45 minutes, high impact, no gatekeeper
- The one industry-specific database relevant to you — varies, but your industry probably has one
- Wikipedia draft — spend 3 hours preparing the draft; accept that it may take 60-90 days to go live
Those three alone typically move AI citation rate from near-zero to 15-25% within 90 days for targeted queries. The other seven are additive but less critical at the starting line.
What about sites like Reddit, Hacker News, Substack?
These aren't "places AI models look" in the same sense as Wikipedia — they're dynamic, mention-driven sources rather than structured databases. But they do matter. AI models reference fresh discussion on these sites for recency, sentiment, and community validation. Earned mentions on Reddit, HN, or popular Substack newsletters function like third-party editorial citations.
Don't spam them. Earn organic mentions by contributing thoughtful content, launching publicly, or publishing research others reference.
The audit approach
To diagnose where you stand across these 10 sources, a 15-minute audit:
- Search each platform for your company name. Record: not present / incomplete profile / complete profile.
- For platforms where you're complete, check for recency. Last updated > 12 months is stale.
- For platforms where you're absent, estimate effort to join.
- Prioritize using the matrix above.
A structured GEO Report at SEOGrade includes this audit across all 10 sources plus the citation-rate baseline across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews. If you'd rather DIY the entity claims, the audit at least tells you where to start.
FAQ
Q: Can I fake entity presence? No. Creating fake Wikipedia articles gets them deleted within days and can earn you a domain-level penalty. Creating fake Crunchbase or Trustpilot content can get your profile banned. Work with real signals.
Q: What if my industry's leading directory is a pay-to-play directory? Evaluate case by case. Some are worth the paid listing fee; some are shakedowns. Generally: if the directory has editorial judgment (reviewers, rankings, moderation), it's worth paying. If it's purely "pay us to appear," it often isn't.
Q: Does claiming entity presence help with Google SEO too? Some. Crunchbase and LinkedIn carry backlink equity. G2 and industry directories do too. But the primary value is AI citation, not classic SEO.
Q: How often should I update my entity profiles? Every 6 months at minimum. Update: headcount, new products, recent funding, updated description.
Q: What's the minimum-viable version of all this? Crunchbase + LinkedIn + one industry-specific database. Everything else is additive.
Most of these claims are 30-60 minute projects. You can make enormous GEO progress in a single focused week if you batch them. If you'd rather have a customized prioritization with the 25-query AI visibility baseline to prove it's working, the SEOGrade GEO Report is $149 at the Starter tier. Most operators don't need it — they just need to be told what to do next. This list is what to do next.