AI-powered meal planning from pantry photos

Reduce food waste by turning existing ingredients into personalized meal plans

Pledged

$847k

56% of $1500k

Feedback

Net score: +124

Traction

340

Beta users

Retention

68%

Weekly active

Business Details

Problem

40% of food purchased in US households goes to waste. Planning meals around existing ingredients is time-consuming and requires culinary knowledge most people don't have.

Solution

Users photograph their pantry and refrigerator. Computer vision identifies ingredients. AI generates recipe suggestions optimized for their dietary preferences, skill level, and time constraints. Real-time inventory tracking prevents duplicate purchases.

Market Opportunity

US food waste costs households $1,600 annually. Target addressable market: 45M households actively seeking to reduce expenses and environmental impact. Initial focus on urban millennials and Gen Z (18M households, avg. income $75k+).

Target Customer

Time-pressed professionals aged 25-40 who cook 3-5x weekly, care about sustainability, and are comfortable with mobile-first solutions.

Business Model

Freemium SaaS. Free tier: 3 meal plans/week. Premium ($9.99/mo): unlimited plans, grocery delivery integration, nutritionist-reviewed plans. Affiliate revenue from grocery partners (est. 3% commission).

Current Traction

Built MVP, 340 beta users, 68% weekly retention, avg. 4.2 meals planned per user per week. Early partnership discussions with Instacart and Whole Foods.

Founder

Sarah Chen

MIT Computer Science, Stanford MBA

8 years professional experience

Background

Previously ML engineer at Google (2016-2021), focusing on image recognition systems. Led a team of 6 building real-time visual search. Left to pursue consumer AI applications after experiencing personal frustration with meal planning inefficiency.

Previous Ventures

No previous ventures listed

Notable Achievements

Led ML team at Google, 5+ years experience in computer vision

Investor Feedback & Capital Commitments

Community evaluation and financial pledges

Investor

Feedback

Sentiment

Capital Pledged

james_vc

2 days ago

Strong product-market fit. Food waste is a $400B problem globally. Computer vision accuracy will be critical—have seen similar startups fail on this. Team needs a food science advisor. Monetization path is clear.

Net: +31

$250.0k

29.5% of total

maria_angel

3 days ago

Love the sustainability angle but concerned about unit economics. $9.99/mo feels low given CAC in this space typically runs $40-60. Would need to see cohort analysis. Partnership strategy with grocers is smart—could be the real business here.

Net: +20

$150.0k

17.7% of total

tech_operator

4 days ago

Execution risk is high. Image recognition for food items is harder than it looks—lighting, packaging variations, partial visibility. Recommend pivoting to barcode scanning first, then layer in CV. Founder has right background though.

Net: +7

$75.0k

8.9% of total

consumer_focused

5 days ago

Tested the beta. UX is excellent. Recipe quality beats Yummly and Paprika. Retention numbers are exceptional for this category. If they can nail grocery integration, this could be a $100M+ exit to Instacart or a major grocer.

Net: +40

$200.0k

23.6% of total

skeptical_investor

1 week ago

Market is crowded. Mealime, Supercook, BigOven all tried this. What's the moat? CV models are commoditized. Without proprietary data or exclusive partnerships, this gets copied by Google/Amazon in 18 months.

Net: -8

No pledge

product_builder

1 week ago

The traction speaks for itself. 68% weekly retention in food tech is rare. Users are clearly getting value. Would want to understand churn reasons and see NPS data. Willing to lead seed round if metrics hold for another 8 weeks.

Net: +34

$172.0k

20.3% of total

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