Why Cheers
Built because customers stopped Googling.
AI has rewritten the rules of local discovery. When a customer asks ChatGPT or Gemini for a recommendation, the answer depends on your reputation layer: the website, reviews, listings, structured data, and local content. Cheers measures that layer, handles the agreed work, and rechecks how your business appears.
The founders
We've been here before.
We've built reputation software for frontline teams before. Now we're building the platform that makes businesses visible to AI.
How it works
Three moves that strengthen your public evidence.
Not just software.
We review your citations, reviews, and structured data to understand the public evidence AI systems can use. Then we build a scoped plan and remeasure the same priority questions.
Where service happens.
Your team gets simple tools to collect reviews at the point of service. NFC taps, mobile flows, whatever fits your operation.
Outcomes, not averages.
Badge, QR, and tracked-link workflows can connect review requests to the employees and locations that earned the interaction, giving operators clearer coaching and investment signals.
Case study
Hello Sugar runs reputation operations across hundreds of local salons.
The difference
Why teams choose Cheers.
Software plus execution
Technology that measures local visibility, paired with scoped execution across the evidence gaps Cheers agrees to handle.
AI-native
Backed by Y Combinator. Built from day one around how AI models interpret reputation signals.
Technical approach
We focus on the technical signals AI actually uses to decide who to recommend. Not guesswork.
Frontline focus
Built for serious local service operators, from established single-location businesses to multi-location brands with distributed teams.
See where AI is ignoring you.
Run a free visibility scan to see whether recommendation engines include your business today.