Restaurant/Grocery Menu and Ordering API for 1.1M Stores (US and CA)

Hacker News

We spent the past 5 years developing technology to pull real-time menus/grocery store inventory and submit orders. We first made a consumer app that helped you to find the best online ordering deal, and we would link you out of the app (Like KAYAK). Then, we decided we needed to have ordering on our app, so we built the tech to get menus/inventory and send in orders (Like Expedia). We grew our app to 1,210,200 users and decided to pivot B2B and offer other companies the ability to pull menus/inventory and send in orders. We now have dozens of companies such as TripAdvisor using our API. Here are a few live examples: Restaurant-- https://www.tripadvisor.com/Restaurant_Review-g30196-d873164... (click "Order Online") Grocery-- https://myallen.jupiter.shop/recipe/b48d9a29-9f60-4866-9fdf-... (Entire inventory and add checkout feature is powered by MealMe)

Visit product View on Hacker NewsApr 27, 2024

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

64%64% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Hacker NewsStrong engagement from HN community · Strong signals: ide · Missing: https docs, excited, just released

59%59% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal

46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive

44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: user, using · Missing: mac, agents, macos

36%36% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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