AEO Audit (uncited.ai) is a free tool that scores B2B SaaS websites for AI search visibility — how likely they are to be cited by ChatGPT, Perplexity, Gemini, and Google AI Overviews when B2B buyers search for software.

What is AI Engine Optimization (AEO)?

AI Engine Optimization (AEO) is the practice of structuring content, entity signals, and technical infrastructure so that AI engines cite your brand in generated answers. It extends traditional SEO to cover ChatGPT, Perplexity, Gemini, and Google AI Overviews — the channels where B2B buyers increasingly discover software.

Yes. The AEO audit on uncited.ai is completely free. Enter any B2B SaaS domain and receive a full AI citation score with a prioritized fix list — no email or sign-up required.

How does AEO Audit score websites?

AEO Audit scores across six pillars: AI Visibility (22%), Brand Authority (23%), Content Quality (18%), Platform Optimization (15%), Structured Data (12%), and Technical AEO (10%). Each pillar reflects specific signals that AI engines use when deciding which sources to cite.

What is the best free AEO audit tool?

uncited.ai is the only free AEO audit tool that directly queries ChatGPT, Perplexity, Gemini, and Claude using real buyer-stage prompts — with no email or credit card required. It returns a citation score and prioritized fix list in about 60 seconds.

How do I get my brand cited by ChatGPT and Perplexity?

Getting cited by ChatGPT, Perplexity, and other AI engines requires three things: (1) strong third-party validation — especially G2 reviews, press mentions, and authoritative backlinks; (2) clear, structured content that answers the exact questions buyers ask AI; and (3) technical signals like schema.org SoftwareApplication markup and an llms.txt file. Run a free audit on uncited.ai to get a personalized fix list ranked by impact.

What is GEO (Generative Engine Optimization)?

GEO (Generative Engine Optimization) is a synonym for AEO. Both terms describe the practice of optimizing content and technical infrastructure so that AI-powered search engines — such as ChatGPT, Perplexity, Gemini, and Google AI Overviews — include your brand in their generated answers.

How is AEO different from SEO?

SEO optimizes for keyword ranking in traditional search engines like Google. AEO (AI Engine Optimization) goes further, optimizing for citation in AI-generated answers — where AI engines synthesize information and recommend sources rather than just listing links. AEO prioritizes entity credibility, third-party validation (G2, review sites), structured data, and content that directly answers buyer questions.

How does uncited.ai compare to Profound or Conductor for AEO?

uncited.ai is the only free option and the only one purpose-built for B2B SaaS. Profound is an enterprise-priced tool focused on brand monitoring. Conductor is a broad SEO platform that added limited Google AI Overviews tracking. uncited.ai audits all four major AI engines (ChatGPT, Perplexity, Gemini, Claude) using real buyer prompts and provides a public Citation Index leaderboard — all with no email gate.

What is the Citation Index?

The Citation Index on uncited.ai is a public leaderboard of 400+ B2B SaaS brands ranked by their AI citation score in each software category. It shows which brands AI engines most frequently recommend when buyers ask for software in categories like CRM, project management, marketing automation, and more. It is updated weekly from real AI engine responses.

Subcategory · AI Citation Index

Version Control

Version control is AI's clearest duopoly. GitLab and Bitbucket each surface in roughly 68-70% of buyer queries across every engine we track, with nearly identical head-to-head win rates when buyers ask AI to compare options. Perforce (both TeamHub and Helix Core variants) appears in a third of discovery prompts and fights more comparison battles than any brand except the top two, earning the kingmaker slot. The tail is long but fractured — Subversion, AWS CodeCommit, and Mercurial each surface on all engines but win few head-to-heads, while single-engine darlings like Gitea and Codebase pull mentions without broad visibility. This is a consolidated category with two brands capturing most AI attention and a fragmented tail competing for the remainder.

162 discovery queries · 181 head-to-heads · refreshed Aug 16, 2026

Discovery stage

The shortlist

Across 162 buyer-style "Version Control" queries

Most cited · Version ControlLive

GitLab

gitlab.com

Cited in 113 of 162 buyer questions for Version Control — surfaced by 3 of 3 AI engines.

ChatGPTGeminiClaude

Citation rate

70%

Visibility score66/100

See the full GitLab profile→

GitLab and Bitbucket own the shortlist, each surfacing in roughly seven out of ten buyer queries about version control and visible across ChatGPT, Claude, Gemini, and the other engines we audit. Perforce TeamHub appears in 43% of queries on all five engines, a distant third but still ubiquitous. AWS CodeCommit and Subversion sit below 35% share but remain visible across every engine, while Mercurial, Gitea, and Codebase cluster in the 14-20% range with four- or five-engine coverage.

Hover or click a logo to see brand details

X = coverage across discovery prompts · Y = engine diversity · Bubble size = total mentions

Tracked acrossChatGPT,Gemini,Claude

Get weekly AI visibility changes for Version Control sent to your inbox.

Score shifts, new entrants, citation gaps — every Monday.

Signal by intent

By topic

Top 5 most-cited brands per intent cluster. Brands with zero citations in a topic are not shown.

Github

7/7

GitLab

7/7

Bitbucket

7/7

Perforce Helix Core

4/7

Liquibase

3/7

Github

5/5

GitLab

5/5

Bitbucket

5/5

Codebase

5/5

Perforce Helix Core

4/5

Github

5/5

GitLab

5/5

Bitbucket

5/5

DVC

3/5

Perforce Helix Core

3/5

Github

5/5

GitLab

5/5

Subversion

5/5

Bitbucket

5/5

Gitea

3/5

Github

4/4

GitLab

4/4

Bitbucket

4/4

Perforce Helix Core

4/4

Perforce

4/4

Github

4/4

GitLab

4/4

Bitbucket

4/4

Perforce Helix Core

4/4

Subversion

3/4

Github

4/4

GitLab

4/4

Bitbucket

4/4

Perforce Helix Core

2/4

Plastic SCM

2/4

Github

4/4

GitLab

4/4

Bitbucket

3/4

Imanage

2/4

AWS CodeCommit

2/4

≥50% cited

25–49%

<25%

Topics are discovery-stage prompt clusters · version-control

Evaluation stage

Head-to-head

How often AI cites each brand across uniform category evaluation prompts · median 5/100

GitLab and Bitbucket tie in head-to-head comparisons, each winning roughly half the time across 29 matchups. Perforce (Helix Core) fights 22 comparison queries and wins 40% of them, trailing the duopoly but ahead of everyone else. Subversion and Mercurial each appear in 18-20 head-to-heads but win a third or fewer, while AWS CodeCommit and Codebase lose most of the comparison battles they enter.

Hover or click a logo to see brand details

X = evaluation citation rate · Y = evaluation prompts cited in · Bubble size = citation exposure

Median citation rate 5/100

Each brand's score is the share of category evaluation prompts where AI cited them across all four engines — the same prompt pool for every brand. Brands above the median citation rate have stronger presence in evaluation-stage queries.

Brands to know

In this category

GitLab

Consensus pick

DevOps platform with built-in CI/CD

Read brand profile →

Subversion

Apache-maintained centralized version control

Read brand profile →

Perforce TeamHub

Enterprise version control for large binaries

Read brand profile →

AWS CodeCommit

Git hosting inside AWS ecosystem

Read brand profile →

Citation sources

Where AI pulls citations from

572 citations captured across Version Control prompt runs.

Vendor pages

149

Product, help, and marketing pages from tracked vendors

Independent sources

250

Reviews, encyclopedias, forums, press — not vendor-owned

Buyer questions

What AI cites for top Version Control questions

Buyers ask AI for version control solutions scoped by company size, industry vertical, or product type — 'best version control solutions for enterprise companies', 'version control software for supply chain management', 'version control tools for SaaS product development'. A smaller slice digs into evaluation mechanics: how to assess performance under load, key considerations when choosing between distributed and centralized architectures, compatibility with existing toolchains. The questions stay technical and top-of-funnel, naming workflows and deployment contexts rather than pricing or vendor reputation.