Hint, an AI assistant for homeowners co-founded by Martha Stewart, launched on iOS today with $10 million in funding and a product built around home maintenance, insurance, energy, and document management. The startup pairs Stewart's home and hospitality expertise with a technical team led by CTO Kyle Rush, formerly of Casper and Maisonette, and CEO Yih-Han Ma, previously an SVP and GM at Red Ventures. The app is free, with no subscription and no ads at launch.
The company originally started in 2024 as a tool to help homeowners navigate decarbonization incentives, then pivoted when the team realized the same interface could manage the whole house. The pivot is the entire product thesis — that homeowners don't have a single app that knows their address, their appliances, their soil, their insurance, and their documents.
On setup, Hint pulls public data tied to the user's address — property records, weather, soil composition, utilities — and builds a profile of the home. Users then upload inspection reports, warranties, mortgage documents, insurance policies, and invoices, all of which become queryable through the in-app AI assistant. Photos of major appliances feed a personalized maintenance schedule with push notifications for tasks like flushing a water heater or vacuuming refrigerator coils.
Key facts
- 01Hint launched July 29, 2026 with $10M in funding from Montauk Capital, Slow Ventures, Tusk Venture Partners, Energy Impact Partners, Amplo VC, and Hannah Grey.
- 02Martha Stewart is a co-founder with equity, not a financial backer, and reviews the product with CTO Kyle Rush roughly twice a week.
- 03The app runs on OpenAI models for text and Gemini for image work, and is free on iOS with no subscription or ads at launch.
- 04Hint originally started in 2024 as a decarbonization-incentives tool before pivoting to broader home management.
- 05Revenue today comes from an affiliate network of service providers, firewalled from the AI to avoid biasing recommendations.
Stewart's role in the company is operational, not ornamental. Rush says she holds equity, reviews the app on a set cadence, and pushes back when the AI gets something wrong about soil or home systems. She also weighs in on design, branding, and copy. That kind of founder-level involvement is unusual for a celebrity-attached consumer app and is the pitch to consumers who might otherwise dismiss the Stewart tie-in as marketing.
Under the hood, Hint uses commercial libraries from OpenAI for text and Gemini for image tasks — the same stack thousands of consumer AI apps now run on. The differentiation is data assembly and workflow rather than model work: pulling structured facts about a specific address, ingesting user-uploaded PDFs, and generating a maintenance calendar that adapts over time. Hint also produces a single "home score" as a summary metric.
The AI chatbot handles both simple lookups — when the AC was last serviced — and more consequential questions, like whether a HELOC makes sense against current equity, whether a homeowner's deductibles are too high, or whether a specific repair is worth an insurance claim. Those are decisions where a wrong answer has real financial consequences, which puts pressure on the retrieval and reasoning layers to stay grounded in the user's actual documents.
Monetization today runs through an affiliate network of service providers. Rush says the affiliate layer is firewalled from the AI so recommendations aren't biased by payout. The plan is to keep the core intelligence free and introduce a premium subscription later for power users managing multiple properties.
“We want it to be in the hands of every homeowner in the country.”— Kyle Rush, Hint co-founder and CTO
The $10 million round is backed by Montauk Capital, Slow Ventures, Tusk Venture Partners, Energy Impact Partners, Amplo VC, Hannah Grey, and Brian Kelly of The Points Guy. That investor mix — climate, consumer, and travel-adjacent — reflects Hint's origins in decarbonization and its ambition to sit at the intersection of home services, insurance, and energy management.
The obvious risk is scope. Home management touches insurance advice, financial products, energy purchasing, and safety-critical maintenance, and a general-purpose chatbot answering "should I file this claim" or "is this HELOC a good idea" has to be accurate the vast majority of the time to keep user trust. Hint hasn't disclosed how it evaluates answer quality on those higher-stakes queries, and the affiliate model creates an incentive structure that has to stay genuinely walled off from recommendations to hold up over time.
For the broader AI market, Hint is a useful data point on where consumer AI is going after the chatbot phase. The interesting products aren't general assistants; they're vertical assistants that own a data profile — in this case, the house — and turn a general-purpose model into a specialist by feeding it the right context. If Hint lands with homeowners, expect a wave of similar wrappers around cars, small businesses, and personal finances, each betting that the moat is the data assembly and the workflow, not the model.
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