Measure and automate AI visibility
Most AI visibility tools tell you what happened and stop there. Omnipresence shows you what to do about it, then hands the work to your own agent so it actually gets done.
Knowing your number dropped doesn’t tell you what to fix
So your mention rate drops. On its own that doesn’t help you much. What you actually need is the query you lost, the page that beat you, and something that will go and fix it.
More than a tracker
Most trackers give you a mention rate and that’s about it. It’s a scoreboard. It doesn’t tell you what to go and change, and that’s where pretty much every tool in this category stops.
Omnipresence connects everything
We join every prompt to the queries it fired and the sources those queries pulled back. It’s one graph, end to end. So the gap between where you’re getting cited and where you’re not turns into a work list.
Then your agent implements
You hand a target to your own agent over MCP, and the skills to act on it come with it. So the fix actually ships instead of sitting in a report.
Start with the prompts your buyers actually type
Add as many as you need and set how often each one runs. You bring your own API keys, so you’re paying the API directly and you can see exactly what a run costs.
- Track as many prompts as you need. There’s no per-prompt pricing.
- Set the cadence per prompt, anywhere from daily to monthly
- Bring your own keys, and see exactly what each run costs
- Mark any prompt as a control so it never gets optimisation work
See the queries and sources behind every answer
A prompt is never just one search. The model fans out into its own queries, and each of those reads its own sources. We record all of it, so you can see which queries actually decide your category and which pages keep winning them.
- Every fanout query the model fired, and how often it fired
- Discovery and verification queries kept separate
- Every source attributed to the query that surfaced it
- Your pages marked against everyone else's
Pick a target, hand it to your agent, get it done
Pick the fanout you want to win and pass it to your agent over MCP. The skills to act on it come with it. No prompt engineering, no copying context between windows.
- Update your site, against the sources that are winning today
- Target existing sources the model keeps reading
- Create the competing source where none is good enough
One tracked prompt, the queries the model actually fired, and the pages it read to answer.
Everything the agent does is logged against the number it moved
Every action gets logged with the page, the date and the target it was aimed at. So your team can see what’s being worked on, and it sits on the same timeline as the measurement it belongs to.
- Work logged with page, date and target
- Optimisation markers land on the same chart as the mention rate
- Control prompts stay untouched, so a lift is actually attributable
- Pull any of it for reporting through the same connection
A private room, included with your subscription
You get the workflows, the teardowns and Chunk Score, plus a weekly call on what’s actually working in AI search right now. Every call is recorded, so joining late isn’t a problem.
See what is inside
How AI search actually works
Experiments we ran ourselves on what actually moves AI visibility, and what doesn’t.
10x AI Visibility Refresh
What Happened When We Refreshed 98 Posts and Published Nothing
98 posts refreshed, zero pages published, citations up 10x in 91 days. The correlation between Google rank and AI citation was effectively zero, and 41 cited pages had no Google impressions at all.
Read the report
The Credibility Layer
How ChatGPT Recommends Local Businesses
200 reasoning sessions, 5,933 logged searches, 1,982 citations. Rank barely touches recommendations, Reddit was cited zero times, and every recommendation turned out to be a 30 search credibility audit.
Read the report