Martha Stewart has co-founded Hint, an AI app that launched today to help homeowners manage maintenance, energy use, insurance, and documents. The app builds a personalized home profile from public data and documents, then uses an AI chatbot to answer questions about appliances, maintenance schedules, and home finances. Stewart is an active, equity-holding co-founder who reviews the app twice weekly; the startup raised $10 million（約16億円） and plans to keep core AI features free while adding a paid tier for power users.
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Martha Stewart has joined the co-founding team at Hint, a new AI app that launched today to help homeowners manage maintenance schedules, energy use, insurance claims, soil and air quality, and store home-related documents. Stewart is an equity holder and active contributor—not a figurehead—who reviews the app twice weekly and provides feedback on accuracy, design, and language.
Why it matters
Homeowners typically lack a single app to manage their homes' upkeep and decision-making. Hint builds a home profile from public data (property records, weather, soil), lets users upload inspection reports and warranties, and uses an AI chatbot to answer questions ranging from appliance maintenance details (like vacuuming refrigerator coils to prevent fire) to financial questions (like whether to tap home equity). Stewart's decades of home-management expertise directly shaped the app's development.
What to watch
The app is free today and available on iOS; the plan includes a paid tier for power users (such as managing multiple properties) and affiliate revenue from service provider partners, which Rush says is separate from the AI recommendations. Hint raised $10 million（約16億円） in funding from investors including Brian Kelly (The Points Guy), Slow Ventures, and others.
Martha Stewart's involvement in Hint signals a shift in how celebrity figures engage with AI startups—rather than a lightweight endorsement, she is a working co-founder who directly shapes the product. The app itself addresses a genuine gap: homeowners lack a unified platform to track maintenance, understand property risks, and make decisions about insurance and energy. By combining public data (property records, soil composition, local climate) with user-uploaded documents and appliance photos, Hint creates a personalized context that an AI can use to answer both mundane questions (when to replace a refrigerator water filter) and complex ones (whether filing an insurance claim makes sense). Stewart's expertise in home management—her core professional domain—becomes the app's quality-assurance mechanism, catching errors about soil and appliance care that a generic AI might miss. The startup's earlier pivot from a decarbonization-incentive tool to a broader home-management platform reflects a common observation in AI development: the real value lies in solving a concrete, everyday problem rather than a narrowly focused one. Hint's business model—free core AI, future paid tiers for power users, and affiliate revenue from service providers—is designed to scale without biasing recommendations, a structural safeguard the founder emphasizes.
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