Cross-platform model coverage
Track major answer engines and model-specific ecosystems from one operating layer
AI search position
See where AI answer engines recommend your brand and what evidence shapes the outcome
Scoped by category competitors and priority platforms
Category benchmark
ChatGPT
86%Mentioned in 4 of 7 category queries
Perplexity
72%Competitor cited more frequently
Gemini
64%Inconsistent source coverage
DeepSeek
58%Not appearing in priority answers

Assessment preview
















Coverage proof
Compare how answer engines mention cite recommend or omit your brand across models and platforms
Track major answer engines and model-specific ecosystems from one operating layer
Focus on comparison scenario and recommendation prompts tied to buyer decisions
Keep evidence current as models sources and rankings shift
Product comparison
Buyers compare options and ask for recommendations
3/5 sources
Evidence coverage sufficient
2024 06 01
13 42 18
Vendor evaluation
Teams check fit feasibility cost and risk
2/4 sources
Some evidence paths covered
2024 06 01
11 07 33
Risk review
Decision makers look for proof and assurance
1/3 sources
Not cited in this path
2024 06 01
09 21 44
TIME RANGE 2024 05 25 TO 2024 06 01 | SCOPE GLOBAL | FRESHNESS 2H AGO
Coverage status is inferred from answer evidence and source citations
AI engines
Compare how each engine cites sources frames competitors and handles category evidence
Priority
4 engines
Checks
16 signals
Method
Separate lanes
OpenAI
Narrative framing shapes recommendation presence
Perplexity AI
Source quality and freshness change citation share
Entity consistency connects search and answer signals
DeepSeek
Divergence reveals model specific coverage gaps
Each row keeps model behavior separate so one engine cannot hide another engine gap
Compare all platformsDecision views
Turn noisy AI responses into position platform perception and source evidence
Position
Evaluate the prompts that shape buyer decisions in your category
Platforms
Compare how major AI systems frame rank or omit the brand
Perception
Track recommendation patterns sentiment and framing across platforms
Sources
Identify citations articles and pages that shape category answers
Operating loop
Define priorities collect cross platform responses and turn evidence into execution
Map prompts around buyer journeys comparisons and category scenarios
Capture answers across priority AI platforms
Create a stable reference for future position changes
Separate leadership signals from team level detail
Turn visibility gaps into briefs pages and source work
Connect publishing activity back to AI search position
Decision proof
Compare competitive position coverage gaps and source influence in one layer

Position view
See leadership absence and competitor pressure in the prompts that matter

Coverage view
View coverage by prompt and platform without reducing evidence to one score

Source view
Identify citations articles and domains shaping model confidence
Start with a focused assessment for your brand category competitors and priority platforms
We scope the assessment with your team before work begins