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Featured Case Study AI/ML Product

PlanEat AI

Building an AI-powered meal planning assistant that generates personalized recipes, shopping lists, and nutritional insights—shipped to production in 6 weeks.

6
Weeks to Launch
$1.2M
Pre-Seed Raised
50K+
Monthly Users
4.8
App Store Rating

App Screenshots Coming Soon

The Challenge

The founding team came to us with a vision: democratize healthy eating through AI. They had domain expertise in nutrition but needed a technical partner to bring their product to life—fast. They had 8 weeks of runway and needed to ship.

The Core Problem

Existing meal planning apps required hours of manual input. Users wanted intelligent suggestions based on their dietary preferences, what's in their fridge, and their health goals—without the friction.

Our Approach

We applied our standard playbook: diagnose, blueprint, construct, scale. But with a 6-week deadline, every decision had to be ruthlessly prioritized.

Week 1-2: Discovery & Design

  • User interviews with 20 target customers
  • Competitive analysis of 15 meal planning apps
  • High-fidelity Figma prototypes for core flows
  • Technical architecture decisions (Next.js + Supabase + OpenAI)

Week 3-5: Development Sprint

  • Built AI recipe generation pipeline with GPT-4
  • Implemented real-time meal plan customization
  • Created automated shopping list generation
  • Integrated nutritional analysis APIs

Week 6: Launch & Iterate

  • Production deployment with monitoring
  • Analytics setup (PostHog, Sentry)
  • Beta user onboarding and feedback loops
  • Rapid iterations based on user data

Tech Stack

Next.js 14 TypeScript Supabase OpenAI GPT-4 Tailwind CSS Vercel Stripe

The Result

PlanEat AI launched on schedule, gained 10,000 users in the first month, and helped the founders close their $1.2M pre-seed round.

Mission Accomplished.

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