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Momos Guest AI redefines guest experience at every location, helping businesses streamline operations and enhance customer interactions.
Momos has raised $16.5M across 2 funding rounds.
Momos has raised $16.5M in total across 2 funding rounds.
Momos has raised $16.5M across 2 funding rounds. Most recently, it raised $10.0M Series A in September 2024.
| Date | Round | Lead Investors | Other Investors | Status |
|---|---|---|---|---|
| Sep 1, 2024 | $10M Series A | 645 Ventures | Bascom Ventures, Costanoa Ventures, Cubit Capital, Greylock, Infinite Capital, Lerer Hippeau, Liquid 2 Ventures, Lockheed Martin Ventures, LombardStreet Ventures, Metaplanet | Announced |
| Aug 27, 2021 | $6.5M Seed | — | — | Announced |
Momos has raised $16.5M in total across 2 funding rounds.
Momos's investors include 645 Ventures, Bascom Ventures, Costanoa Ventures, Cubit Capital, Greylock, Infinite Capital, Lerer Hippeau, Liquid 2 Ventures, Lockheed Martin Ventures, LombardStreet Ventures, Metaplanet.
Momos is an AI-powered customer experience management (CXM) platform designed for multi-location brands in restaurants, quick-service restaurants (QSRs), hospitality, beauty, wellness, healthcare, food and beverage, and retail. It builds tools for customer service, feedback collection, reputation management, analytics, marketing automation, and case management, solving the problem of fragmented customer interactions across locations by unifying them into a single AI-driven stack that automates responses, recovers revenue from unhappy customers, improves CSAT, and drives loyalty.[1][2][3][4] Serving brands like Shake Shack, Baskin-Robbins, Wendy's, Firehouse Subs (now live at 1,350+ North American locations), and over 600 others across 20,000+ global locations, Momos has shown strong growth momentum with $10M in total funding (including a $6.5M seed round co-led by Sequoia Capital India and Alpha Wave Incubation) and expansion from APAC to North America.[1][2][4][5][6]
Founded in 2020 and based in Singapore (with headquarters now in San Diego, US), Momos emerged from the founders' hands-on experience scaling restaurant operations in Southeast Asia. Co-founder and CEO Sai Alluri, an early Uber employee, led restaurant operations at Grab, managing hundreds of locations and identifying gaps in customer engagement tools. Teammates include co-founder Andrew Liu (finance expert at Grab focused on food), Grant Oliveira (Head of Product, ex-Microsoft), Leland Tran (Head of Engineering, ex-Intuit), and David Dubinski (Head of Sales).[2][5] Early traction came from APAC giants like Shake Shack and Salad Stop, evolving into global wins like the May 2025 Firehouse Subs rollout, fueled by the founders' "hustle" in F&B tech and a mission to digitize customer lifecycles.[1][5][6]
Momos rides the AI-driven digital transformation of hospitality and multi-location retail, where fragmented customer data hinders scale amid rising eCommerce-ization of F&B—projected to grow as QSRs and chains digitize post-pandemic. Timing aligns with AI adoption for CXM, as brands face labor shortages and demand personalized, 24/7 service; Momos capitalizes on market forces like review-driven revenue (e.g., Google/Yelp impact) and omnichannel expectations.[1][2][6] It influences the ecosystem by powering major chains' expansions (e.g., Firehouse Subs' national launch), setting standards for AI in ops, and bridging APAC-US growth, much like Capillary Technologies in loyalty but with stronger AI automation for service.[1]
Momos is poised for hypergrowth as AI CXM becomes table stakes for multi-location brands, with next steps likely including deeper North American penetration post-Firehouse Subs, product expansions into predictive analytics, and further funding for global hires (51-200 employees now). Trends like agentic AI and real-time ops will amplify its edge, potentially evolving it into a full revenue platform influencing how chains like Wendy's compete on experience. From its Grab-inspired roots, Momos exemplifies how operator-led AI tools are reshaping hospitality scale.[1][2][5]
