The problem

The solution

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The problem

The solution

Get the report

Resources

Talk to us

Agents for world-class hospitality

Every great restaurant brand knows what unreasonable hospitality looks like - they've seen it at their best location, their best shift, their best crew. The problem was never ambition. But delivering it at scale, across all channels and locations, was too expensive and out of reach. Our agents close this gap.

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Momos helps leading brands get better with every guest

Agent Alfie

The Experience Agent

Agent Rockie

The Intelligence Agent

Agent Rosie

The Operator Agent

What 30,000+ locations reveal

World-class hospitality used to demand unreasonable cost

Restaurant brands were built to deliver world-class offline hospitality. Online customer service is a fundamentally different problem — one they were never designed to solve.

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It's economically impossible

Restaurant margins don't support the tooling or headcount enterprise CS requires — and at the incident level, manual recovery costs more than it returns. You can't spend $8 to recover a $12 order.

The volume is impossible to manage manually

Millions of touchpoints across platforms — manual management is impossible at scale

Consistency can't be a people strategy

At 80% annual turnover, world-class hospitality can't depend on who's working that shift.

Without a feedback loop, every mistake repeats.

Incidents get resolved. Patterns never do.

Too many human layers slow every response.

Multi-user workflows and approval gates add friction at every step — by the time a resolution clears the chain, the recovery window has closed.

Existing tools weren't built for this.

Most software was designed for ticket tracking, not hospitality. It measures response volume, not whether the guest came back.

Outcomes

When guest experience stops being a gap and starts being a system, the dollars follow

71%

avg. guest return rate after 1-hour recovery

$150K

avg. recoverable revenue per location annually

128%

avg. ROI for agentic AI adopters

The solution

World-class guest experience. Resolved, understood, and closed — automatically.

Alfie recovers. Rockie surfaces. Rosie closes. That's unreasonable hospitality, made systematic.

Alfie
Experience Agent
Instant, 24/7 resolutions
Knows every guest
Plugs into your existing stack
Avg. response <4 min
63.5% guest return rate
Rockie
Intelligence Agent
Instant intelligence
Surface incidents, root causes & risks
Personalized operator reports
Coming soon
Rosie
Operator Agent
Tell your team what to do
SOPs, tasks, and impact tracking
Increase repeat visits
Coming soon

Sarah

Honestly let down by last night's experience. Felt like just another table.

Alfie

That's on us, Sarah. You've got 500 points coming your way plus a dinner for two, on the house. Can I get that booked for you?

Alfie

Experience Agent

Instant, 24/7 resolutions

Knows every guest

Plugs into your existing stack

Avg. response <4 min

63.5% guest return rate

Alfie

Experience Agent

Instant, 24/7 resolutions

Knows every guest

Plugs into your existing stack

Avg. response <4 min

63.5% guest return rate

Rockie

Pulled up 2 locations with a drop. Want me to break them down?

Avg. Rating

4.7

Alex

Which spots had a CSAT dip last week?

Click send to ask Rockie

AI Credit

1,200 remaining

Rockie

Intelligence Agent

Instant intelligence

Surface incidents, root causes & risks

Personalized operator reports

Coming soon

Rockie

Intelligence Agent

Instant intelligence

Surface incidents, root causes & risks

Personalized operator reports

Coming soon

Total Listings

Processing

Synced

Rosie

Operator Agent

Tell your team what to do

SOPs, tasks, and impact tracking

Increase repeat visits

Coming soon

Rosie

Operator Agent

Tell your team what to do

SOPs, tasks, and impact tracking

Increase repeat visits

Coming soon

Data report

What 30,000+ locations reveal about the brands winning on hospitality

The definitive data case for unreasonable hospitality at scale. Five structural reasons the in-house model fails. The per-location revenue gap. The recovery rate benchmark.

30,000+ locations analyzed

Recovery rate benchmarks

Per-location revenue math

Other resources

The case, built piece by piece

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