MMomos

Papa Murphy’s turned guest feedback into $2 million in recovered revenue with Momos, and Just Salad cut response times by 99% while saving 1,200 hours a month, according to the vendor’s case studies. Momos sells a guest experience platform to restaurant brands, and its AI agent, Alfie, talks to unhappy guests, resolves the complaint and issues a recovery offer in the same conversation.

Momos is best for multi-location and franchise restaurant brands that get feedback across review sites, social media, delivery apps and surveys and cannot answer it all quickly. Points to weigh are pricing by quote, POS and loyalty integrations that the product pages could name more specifically, and results that come from Momos’s own case studies. We rate it 7.8/10 on our scale. We have not used Momos; this review is based on Momos’s product pages and funding coverage.

Customer Outcomes and 2024 Funding Details

Momos publishes customer outcomes on its product pages and disclosed funding details in 2024.

The customer list is the strongest signal. Potbelly, Papa Murphy’s, Just Salad and two unnamed top-five US chains with thousands of locations are not pilots; they suggest Momos can run guest feedback for large franchise systems. Earlier coverage named Shake Shack, Baskin Robbins and Guzman y Gomez as customers.

The funding history adds context. Momos raised a $10 million Series A in September 2024, led by 645 Ventures with Alpha Wave Global and Peak XV returning, bringing its total to $17 million and, at the time, roughly three years of runway. Coverage then reported more than 5,000 businesses using Momos across North America, Asia Pacific and the Middle East, with the US as its fastest-growing market.

The outcome figures are case-study headlines chosen by Momos, and Momos could add how each was measured. The $2 million recovered revenue figure in particular depends on how Momos attributes a returning guest to a recovery offer. Ask for the method behind any number you plan to use in a business case.

A Feedback Inbox With a Review Manager and Alfie

Momos combines a unified feedback inbox with two AI products: the AI Review Manager, which answers reviews, and Alfie, an agent that resolves complaints and issues recovery offers.

Collecting Feedback

Momos brings guest feedback into one inbox from Google Reviews, Yelp, OpenTable and TripAdvisor; Instagram DMs, Facebook, X, SMS and WhatsApp; delivery apps including Uber, DoorDash, Grubhub, Deliveroo and GrabFood; website chat, the brand’s mobile app, contact forms, post-visit surveys and phone. AI tags and categorizes each item and sends real-time alerts when sentiment turns negative at a location.

Answering Reviews

The AI Review Manager writes instant replies in the brand voice and tailors them to the guest’s context, with Momos claiming a 100% response rate. It runs around the clock. Brands set the tone and guidelines the replies follow.

Resolving Complaints With Alfie

Alfie handles the conversations that need more than a reply. It understands the issue, speaks with the guest and drives the case to resolution across channels. Through connections to loyalty and POS platforms, it can issue a reward or recovery offer within the same conversation, so a guest with a cold order can receive a credit without waiting for a manager. It pulls visit history, spend and loyalty data to identify high-value guests, sends customizable surveys after visits and tracks whether a guest returns after an issue. When a situation needs a person, Alfie flags it.

A Complaint, Step by Step

A guest leaves a two-star DoorDash review saying fries were missing from a Friday order. The complaint lands in the Momos inbox, tagged as an order accuracy issue at that location. Alfie messages the guest, apologizes, confirms the order and, under the brand’s rules, issues a loyalty credit. The location manager sees the tag in the dashboard. Two weeks later the guest orders again, and Momos records the return, closing the loop. A guest who reports a food safety concern follows a different path: Alfie flags it for a human immediately.

Analytics Across Locations

Because every review, survey and complaint is tagged, Momos can show which locations, dayparts and issues drive negative feedback. For a franchise brand, that turns thousands of scattered comments into a short list of operational problems, such as order accuracy at a handful of stores or slow service on weekend evenings. Real-time sentiment alerts let area managers act on a bad day before it shows up in a location’s star rating.

Onboarding

Momos describes onboarding in stages, from day one through days two to five and into the first week. Brands connect review sites, social accounts and delivery platforms, set response guidelines and decide what recovery offers Alfie may issue.

Pilot Locations First, Then Alfie

A sensible rollout starts with the review manager on a group of pilot locations, where replies are easy to audit, and adds Alfie once response guidelines are settled. The brand then sets recovery rules: which issues earn a credit, how much, and how often one guest can receive one. After a few weeks, compare response times, review ratings and return visits at pilot locations against similar stores without Momos. That comparison gives a brand its own version of the case-study numbers, which is more useful in a budget discussion than any vendor headline.

Managers Set Refund Rules and Handle Allergy Complaints

Managers set the rules for credits and refunds, handle food safety, allergy and legal complaints and fix the operational problems the data reveals. Someone should audit AI replies and offers each week, at least at first, to catch tone problems and offers that are too generous or too stingy.

Quote-Based Sales Without Listed Plans

Momos sells by quote. It does not list plan names or prices on its product pages.

Just Salad’s 1,200 Saved Hours as a Labor Yardstick

Without list prices, the useful math is the labor Momos says it replaces. Just Salad’s case study reports 1,200 hours saved a month. The scenarios below show how to value hours like that; the wage rates are inputs to replace with your own.

• A brand saving 1,200 hours a month: at an illustrative $20 an hour for staff time, that is $24,000 a month, or $288,000 a year, of labor redirected.
• A 50-location group saving 10 hours per location a month: 500 hours a month at $20 an hour is $10,000 a month, or $120,000 a year.
• A 10-location group saving 10 hours per location a month: 100 hours at $20 an hour is $2,000 a month, which sets a ceiling on what the software should cost to pay for itself on labor alone.

Recovered revenue is the other side. If Alfie’s offers bring back guests who would otherwise leave, the value can exceed the labor savings, as the Papa Murphy’s case suggests. The other costs are the recovery offers themselves, which come out of margin, and staff time to set rules and review escalations. Ask Momos for pricing per location and for the cost of any integration work with your POS and loyalty systems.

Momos Compared With Popmenu AI Answering, Yelp Host and Toast IQ

Restaurant AI tools usually focus on one job. Momos focuses on guest feedback and recovery; the others focus on phones or on data inside a POS.

Pick Momos when the problem is guest feedback at scale: hundreds of reviews and delivery complaints across many locations, and no team to answer them quickly. Pick Popmenu or Yelp Host when missed calls are the bigger leak. Toast IQ suits operators who want insights from Toast data. Many brands will run Momos alongside a phone agent rather than instead of one. See our restaurant AI agents guide for more.

Franchise and Delivery-Heavy Restaurant Brands

• Franchise brands: one inbox and consistent replies across hundreds of locations solve a problem franchisees struggle with alone.
• Delivery-heavy brands: complaints from DoorDash, Uber and Grubhub land in the same place as reviews.
• Brands with loyalty programs: Alfie can issue rewards through loyalty and POS connections to win back unhappy guests.
• Marketing teams tracking reputation: tagging and sentiment alerts show which locations and issues hurt ratings.
• International groups: Momos covers delivery apps such as Deliveroo and GrabFood used outside the US.
• Brands with thin guest relations teams: one or two people cannot answer feedback from hundreds of locations; Alfie and the review manager handle the routine volume and leave escalations to them.

Single Independents and Phone-Order Problems

• Single independent restaurants: quote-based pricing aimed at chains is likely more than a single location needs.
• Operators whose main problem is phone orders: a voice ordering agent fits better.
• Buyers who need listed security certifications: Momos has not yet published them on its product pages.
• Teams not ready to set credit rules: Alfie’s value depends on clear rules for offers.

Recovery Offer Caps and Integration Depth

• Offer budgets: cap the value and frequency of recovery offers per guest to prevent abuse by repeat complainers.
• Integration depth: confirm your POS, ordering and loyalty systems are supported before relying on Alfie to issue offers.
• Review platform rules: some review sites restrict incentives tied to reviews; keep recovery offers about the experience, not the rating.
• Sensitive complaints: allergy, illness and injury reports need immediate human handling; check Alfie’s escalation rules cover them.
• Vendor results: the 99%, $2 million and 24% figures are Momos case-study headlines.
• Data handling: Alfie uses visit history, spend and loyalty data; review how guest data is stored and shared.
• Franchisee buy-in: in a franchise system, decide who pays for the platform and who funds recovery offers, the brand or each franchisee, before rollout.

An Agent That Closes the Loop for Multi-Location Chains

For multi-location restaurant brands, Momos goes further than most review tools by letting an AI agent close the loop: talk to the guest, issue a recovery offer and check whether the guest returns. Customers such as Potbelly, Papa Murphy’s and Just Salad, and two top-five US chains, show it runs at scale.

The design choice that sets Momos apart is putting the recovery offer inside the conversation. Most review tools stop at a reply, and a manager has to follow up by email days later; Alfie can settle a routine complaint in minutes, while the guest still cares.

It scores 7.8/10 on our scale. Strong autonomy and channel coverage lead the score, and Momos could raise it by publishing pricing, naming its integrations, sharing security certifications and gathering public ratings. A franchise brand with dozens of locations and a loyalty program is the best fit; ask Momos for references from a brand of similar size and for the method behind the case-study numbers.

Alfie and Automatic Google and Yelp Replies

How Much Does Momos Cost?

Momos does not publish prices. Brands book a demo and receive a quote based on their needs and number of locations.

What Is Alfie by Momos?

Alfie is Momos’s AI agent for guest support. It resolves complaints across channels, issues rewards and recovery offers through loyalty and POS connections, identifies VIP guests, sends surveys and flags cases that need a human.

Can Momos Reply to Google and Yelp Reviews Automatically?

Yes. The AI Review Manager writes instant, brand-approved replies to reviews around the clock, and Momos says it supports a 100% response rate. Feedback from Google Reviews, Yelp, OpenTable and TripAdvisor appears in the same inbox.

Does Momos Handle Delivery App Complaints?

Yes. Momos lists Uber, DoorDash, Grubhub, Deliveroo and GrabFood among its channels, alongside social media, review sites, surveys, chat and phone.

Is Momos Only for Large Restaurant Chains?

Momos is built for multi-location and franchise brands, and its named customers range from regional groups to chains with thousands of locations. Single restaurants are not its main market.