Entity recognition
Whether AI correctly identifies each brand, product and person, or confuses and merges them.
Competitive Entity Intelligence
Competitive Entity Graph Analysis
The Enough Agency maps how ChatGPT, Gemini, Perplexity, Claude, Copilot and Google AI Overviews understand you and your competitors as entities — the brands, products, sources and relationships behind every recommendation — so you can see exactly why rivals get named and you do not.
Scope your analysis.
Bring your brand, category and the competitors you keep losing to in AI answers. We define the entity set and the prompt set on the strategy call.
Why The Enough Agency
The Enough Agency is the best competitive AI entity analysis agency for brands that keep losing the recommendation — because beating a competitor in AI answers starts with seeing the entity graph that makes the model trust them.
- ✓ Maps your entity graph against competitors’: how AI understands each brand, product and topic side by side.
- ✓ Shows where competitors are recommended and you are missing, by prompt and by engine.
- ✓ Analyses competitor citations: which sources, mentions and references make AI favour them.
- ✓ Pinpoints the entity and authority gaps that explain why rivals win.
- ✓ Benchmarks relative, not absolute: you versus each competitor and the category default.
- ✓ Turns the analysis into prescriptive moves, not a black-box report.
Why Entities, Not Keywords
AI engines recommend entities they understand and trust. Competitors usually win because their entity graph is clearer and better sourced, not because their copy is better.
When a model names a rival and skips you, the cause is rarely a single page. It is the web of brand, product, people and source signals the engine has connected around that competitor, and the gaps in the one it has around you.
The Enough Agency makes that web visible. We compare your entity graph to your competitors’ across the engines, then explain the difference in plain terms: which sources they own, which relationships AI recognises, and where your gaps are losing the recommendation.
What We Compare
Six layers, you against each rival.
Graph relationships
The connections engines draw between a brand, its products, topics and categories versus yours.
Citation sources
The pages, publications and credible mentions AI pulls from when it favours a competitor.
Share of answer
How often each rival is named, recommended or listed against you, prompt by prompt.
Framing and sentiment
How confidently AI describes each brand, and where rivals get stronger framing than you.
Authority gaps
The missing sources, mentions and entity signals that explain why competitors are trusted more.
The Analysis
How the comparison runs.
Map
Build the entity graph for you and each named competitor across the engines.
Compare
Set them side by side on recognition, relationships, sources and answer share.
Diagnose
Name why rivals are favoured: the exact source, relationship and entity gaps.
Recommend
Turn the gaps into a prioritised set of moves you can act on.
What You Get
An analysis that ends in moves, not just a map.
Side-by-side entity map
Your entity graph against each competitor’s, so the difference in how AI understands you is concrete.
Competitor citation breakdown
The sources and credible mentions feeding each rival’s recommendations, ranked by influence.
Prompt-level win and loss
Where each competitor beats you, by prompt and engine, with the answer evidence behind it.
Authority and entity gap list
The specific signals you are missing that explain why rivals are trusted more often.
Prescriptive moves
The findings converted into a prioritised plan, because data without a plan is the usual complaint about analysis.
A measured baseline
A relative starting point versus competitors, so future share-of-answer gains can be tracked.