About
Making discoverability something you can see.
SignalRank helps teams understand how they are discovered across search and AI, with clear evidence and practical workflows.
Why we're building it
People increasingly find businesses by asking an AI assistant as well as by searching. For agencies, that creates a new question from every client: are we showing up there?
Answering it well is harder than it looks. AI answers change between runs, cite sources in different ways and can differ by engine. A single screenshot or a blended score can easily mislead.
We're building SignalRank to give agencies a dependable way to measure search and AI visibility, explain it to clients and decide what to do about it.
How we approach it
- 01Evidence before scores
- A number is only as useful as what's behind it. We keep the answers, sources and collection details so every figure can be checked.
- 02Different things, measured separately
- Rankings, mentions, citations, crawler access and referral traffic answer different questions. We report them side by side and never fold them into one score.
- 03Honest about uncertainty
- AI answers vary from run to run. We show sample sizes and confidence ranges rather than precise-looking numbers that don't hold up.
- 04Built for the work that follows
- Measurement should lead to a decision. We design every screen around what an agency does next: fix, publish, report or wait for more data.
Where we are now
SignalRank is in early access. We're working with a small number of agencies at a time, and their feedback decides what we build next.
If you manage search or AI visibility for clients and want to help shape the product, we'd like to hear from you.
Work with us in early access.
Tell us about your agency and the clients you'd track.