Product
AI that explains attribution without inventing credit
The hallucination problem in analytics
Generic AI chat over a CSV will invent confidence. It will suggest pausing a campaign without naming the model, window, or revenue definition behind the claim.
Media teams do not need another opinionated summary. They need answers that point back to the same credit math they already use in the Attribution surface.
What grounded answers look like
Useful questions sound like: which campaigns sit under 0.5x ROAS on last-touch, why linear and last-touch disagree on Meta, or which channels drove closed-won this month.
The answer should cite the model, lookback, and metrics used — then recommend a pause or scale with evidence, not a vibe check.
- Attribution-cited answers from your own first-party behavioural data
- ROAS suggestions tied to spend sync and revenue definitions you control
- No invented credit percentages when the underlying report does not support them
Where Intently draws the line
Intently AI explains revenue and channel performance using your attribution reports and journeys. It cites the numbers; it does not invent them.
That only works when capture, consent, credit, and delivery are already auditable. AI is the last mile of explanation — not a substitute for complete signal.