We were 
Our mission was to decode how meals are prepared and enjoyed at home. Home cooked meals are good for us but too often life is busy so we fall back into familiar patterns of the same few recipes or resorting to unhealthy takeout.
We were dedicated to making it more convenient for people to eat better – which means personalizing variety, diet, nutrition, cost and an assortment of preferences.
We were dedicated to making it more convenient for people to eat better – which means personalizing variety, diet, nutrition, cost and an assortment of preferences.
What we built
Our flagship consumer app was MealHero
Search our collection of over 1 million recipes; browse at your leisure by popularity, cuisine, or preference
Add dishes to your meal plan, map out your week and organize dishes into different meals for each day of the week
Easily shop your entire meal plan with one click to get delivery from Intacart, Amazon, or any of our fulfillment partners
Track your favorite recipes, make notes, and share with your whole family
Available for both iOS and Android
We extended functionality through our web app FridgeToTable
Find recipes by specific ingredients
Look for pantry meals that only need what you already have on hand
Adjust and manage your pantry to keep track of leftovers and what to make next
Use filters to narrow down exactly the type of meal you are looking to make
We built several microapps
One app let users custom build a recipe from scratch, selecting from multiple types of dishes
Desktop
Mobile
Another let users swipe recipes to find new recommendations
Desktop
Mobile
Among others we tried out shopping ingredients by recipe, different forms of guided search, all sorts of methods to bring meals to home chefs.
As a Data Driven organization, every decision revolved around carefully crafted analysis. Every single user experience captured layered data to ensure the best possible journey across our user base
Integrations with Google and Firebase analytics tracking in app user events across mobile devices and the web
A/B testing screens, flows, and new features to dissect decision points and point to proven improvements
Dashboards and reports for different audiences, exported to sources such as Looker for accessibility
Capturing user feedback to combine qualitive data to check and re-check evolving hypotheses
All of our apps were built on top of a robust backend infrastructure utilizing Data Science and Machine Learning
We built an intelligent human-centered and data-empowered platform that adapts to each home chef’s goals and needs enabling better nutrition choices and encouraging cooking at home.
Personal meal solutions - home chefs receive selection of curated, personalized meal options
Culinary understanding - With the knowledge of the culinary world and understanding of dietary preferences, we were able scale to the different unique tastes of home chefs
Recommendation systems - we constantly learned and improved our apps by capturing implicit and explicity feedback, mapping home chef preferences to the food domain as it changes in real-time
Representation learning - Based on learnings from vast food data, we created logical connections and clusters of recipes across multiple dimensions
Item selection & adaption - We seamlessly translated a shopping list into grocery items, including automated ingredient fulfillment
We employed several avenues to reach home chefs through our marketing team and content partners
A rich diverse blog with regular content aimed at inspiring and informing home chefs
Various outreach efforts including coupon stickers with product tie ins
Email and push campaigns that saw recordable impacts on user retention
Dynamic ads that imported user data and directed users to the appropriate app destination
Many cooperative initiaves with content partners to team up and deliver valuable experience to home chefs
It was a wonderful journey and we are proud of all we were able to accomplish! This is not goodbye, just time for the next course..
