What does trakt.ai measure?
trakt.ai measures how brands, products, competitors, topics, and sources appear inside AI-generated answers across prompts, providers, personas, and time.
Answer Engine Visibility
Track visibility, competitor movement, prompt demand, provider divergence, and citation evidence across the questions that shape your market.
Separate model lanes, preserved instead of blended.
The same market question can shift winners when buyer pressure changes.
Rivals move inside the same answer field rather than in separate charts.
See which evidence stabilizes the answer and which sources create drift.
See visibility, provider behavior, competitor pressure, and citation evidence in one view.
Product
Measure answer visibility, provider divergence, competitor pressure, prompt demand, persona lift, and citation evidence without flattening them into one vague score.
Brand visibility across a performance-footwear market, filtered to top-10 answers.
Features
Move from the question to the answer, then into the drivers underneath it: provider behavior, buyer context, competitors, citations, and demand.
Track the questions, buyer lenses, and provider lanes that explain why one answer holds while another shifts.
High-intent comparison question with strong commercial relevance and stable category language.
Workflow
Find the high-signal questions first, compare how answers move across providers and buyer contexts, and keep the evidence tied to competitors, rankings, and citations over time.
Start with the questions buyers actually ask and the demand behind them.
Group the market, competitors, and entities you need to watch together.
Hold the core question steady while separate buyer lenses test answer drift.
Run each provider lane independently so model differences stay visible.
Track rankings, competitors, and citations with enough context to explain movement.
One market question can stay stable across provider lanes while buyer context remains explicit, so answer movement and citation drift stay comparable.
FAQ
Search metaphors break down here. trakt.ai measures answer construction, provider divergence, competitor pressure, and citation evidence directly.
trakt.ai measures how brands, products, competitors, topics, and sources appear inside AI-generated answers across prompts, providers, personas, and time.
No. Provider answers are preserved as separate lanes so teams can compare convergence, divergence, ranking differences, and citation differences.
Prompt volume by proxy is a demand signal built from external market evidence such as keyword volume, related searches, geography, language, and source freshness. It helps teams prioritize which questions matter before they spend cycles tracking answer visibility. It is not native aggregate LLM prompt volume.
A prompt portfolio is an org-owned workspace for a brand, product line, category, campaign, or competitor group. It contains many tracked prompts and personas, then lets teams analyze one prompt in detail or roll results up across the portfolio.
Personas reveal whether different buyer cohorts receive different recommendations, rankings, and citations for the same or similar questions.
Pricing
The limits can move later. The shape is the important part: starter access, a working team tier, and enterprise capabilities for generated personas, drift capture, and prediction work.
per month
For small teams getting signal fast
per month
For active brand and product teams
custom
For multi-brand operators and strategy teams