an AI meal planner for home cooks
What this app does
AI Meal Planner is a meal-planning app for people in the United States who cook at home. Users provide body statistics, activity level, a goal, food preferences, and restrictions, and the app generates a three-day plan with breakfast, lunch, and dinner. It uses real USDA food nutrition lookups for calories and macros and creates a consolidated shopping list in grams that reuses core ingredients across the plan.
As a registered home cook, I can enter and save my body statistics, activity level, goal, food preferences, and restrictions so that the planner can personalize my meals
As a registered home cook, I can generate and view a three-day breakfast, lunch, and dinner meal plan with USDA-backed calories and macros
As a registered home cook, I can view a consolidated shopping list in grams that reuses common ingredients from my meal plan
As an anonymous visitor, I can view the public introduction to the AI Meal Planner before deciding whether to use it
50000
registered_home_cooks
People in the United States who create accounts to save body statistics and dietary preferences, generate meal plans, and use their shopping lists.
20000
anonymous_visitors
Unauthenticated visitors who can view the public introduction before deciding whether to register or use the planner.
How your requirements become a plan and a price
Momen doesn't give a vague quote: it first sizes the project's actual demand for each capability and resource, then costs each item out. The numbers in the 'Project demand' column below — their scale assumptions and derivations — are detailed in Scale & sizing
Minimum viable plan
BASIC
USDA integration and multiple workflows require at least BASIC.
See the capability-by-capability assessment ▾
PROJECT DEMAND
ALLOWANCE PROVIDED (COMPOSITION)
Basic
x 1
Basic is the minimum viable plan
Basic
(Plan tier: BASIC)
See minimum viable plan above
¥ 39
single-tenant kit
x 0
3 req/s
not purchased
(plan/kit 5 req/s)
Covered by plan/kit (margin ~67%)
¥ 0
Database storage add-on
x 1
3.59 GB
10GB × 1/year, amortized monthly
(plan/kit 200.00 MB + add-on +3.39 GB)
Add-on fills +3.39 GB gap beyond plan/kit
¥ 8.33
Object storage
add-on
x 0
0 B
not purchased
(plan/kit 2.00 GB)
No requirement
¥ 0
Outbound data transfer add-on
x 0
0 B/mo
not purchased
(plan/kit 2.00 GB/mo)
No requirement
¥ 0
AI points add-on
x 16
91.1M points
6,000,000 AI Points × 16/month
(plan/kit 97.0M points + add-on +90.1M points)
Add-on fills +90.1M points gap beyond plan/kit
¥ 160
plan + add-ons · usage-based · no development cost
Your options for this project
In the table below, the 'monthly infrastructure' for the self-built / AI routes is derived from the AWS list prices shown below, sized against this project's actual usage. Figures cover infrastructure and operations only — AI usage is billed separately and excluded here, so they don't match the $207.33/mo all-in above.
Current usage sizing
AWS list pricing
2 × t4g.large × 730h
EC2 t4g.large → 98.11
2 × db.m6g.large (Multi-AZ) × 730h
RDS PostgreSQL db.m6g.large → 232.14
3.59 GB-month
RDS gp3 storage → 0.41
0.00 GB-month
S3 Standard → 0
0.00 GB (first 100GB free)
Internet egress → 0
Total ≈ $330.67 / mo
Pure cloud resources
DEVELOPMENT COST
MONTHLY CLOUD INFRA ($/MO)
MONTHLY TOTAL (INFRA + OPS, EXCL. AI USAGE)
Traditional outsourcing / build in-house
about $90,000 - $145,000
≈ $331
Based on the AWS estimate above
≈ $2,331
Infra $331 + ops ~$2,000
4-6 months
5 / 5
Vibe Coding
about $14,000 - $22,000
≈ $331
Based on the AWS estimate above
≈ $1,831
Infra $331 + ops ~$1,500
hours
5 / 5
AI full-stack generation
about $6,000 - $10,000
≈ $331
Based on the AWS estimate above
≈ $1,831
Infra $331 + ops ~$1,500
hours
3 / 5
Off-the-shelf SaaS / vertical solution
$0
N/A
Priced per seat, not by cloud infra
≈ $16,000+
Per-seat pricing, tens of thousands of users
days
1 / 5
Momen
Recommended
$0
$47
All-in: egress / storage / auto-scaling; excludes AI usage
$47
hours
5 / 5
Servers, databases, traffic and storage are inherent infrastructure costs for this project — you pay them whether you outsource, use Cursor or Lovable, or build it yourself (self-built runs ≈ $330.67/mo at AWS list prices, often more), on top of the dev and ops staff you'd need to hire. Momen bundles all of it into $160/mo all-in and removes the need for an ops team.
The frontend can be generated with AI tools (Cursor, Lovable, etc.); the hard part is the backend — auth, database, scaling, data security and ops. Momen delivers a production-grade backend as a BaaS: keep the vibe-coding speed on the frontend, while the backend runs on proven infrastructure — reliable, with no self-hosting or ops.
What scale this estimate assumes, and how the numbers are derived
Cost depends heavily on usage volume. First see the key assumptions and business scenarios this estimate uses, then the full calculation derived from each scenario for every resource — all adjustable to your real situation
We assume 50000 registered accounts because the project description does not provide an explicit user count or a concrete customer base. This is the standard planning assumption for an otherwise broadly applicable consumer SaaS product and can be adjusted when launch or market data is available.
We assume this is a standard linear-growth consumer SaaS product because usage should build as home cooks discover and repeatedly use the planner rather than launching with a full pre-existing dataset. If the product launches with a large imported user and meal history or experiences a short, concentrated adoption burst, this parameter can be adjusted accordingly.
Daily Meal Planning
Daily Meal Planning
Daily Meal Planning
30
times/month
2.33 req/s
Peak load
We assume meal planning is spread across a long daily period because home cooks choose their own planning time rather than responding to an external signal. A 3,600-second window represents the main evening and lunchtime planning period, and the occurrence is daily. The setup, generation, and resulting plan load are kept in one purpose because they are one coherent registered-user journey; the generation action is the core business event while the other actions are prerequisite or follow-up interactions.
Main impact: Peak Concurrency
The scenarios above set the assumptions for each resource; below is the full calculation derived from them. Click to expand each item.
How this app works
What exactly does this budget support? Broken down by business scenario, showing the pages, data tables, automation flows and AI assistant behind each one
Anonymous browsing flow for learning about the meal planner.
Home Page
Primary setup and meal-plan generation flow for registered home cooks.
Home Page
users
meal_plan_generator
save_planner_setup
Review flow for using the consolidated ingredient list.
Home Page
users
page
data_table
ai_agent
action_flow
Home Page
Public introduction page for the home meal-planning service.
Meal Planner Setup Page
Authenticated setup form for the personal inputs used to generate a plan.
Meal Plan Page
Generated meal-plan page showing the three-day schedule and nutrition details.
Shopping List Page
Consolidated ingredient shopping list for a generated plan.
What you might want to know about this project
The Q&A below is generated by AI based on this project's type, features and scale
What will affect this app's resource usage most?
Does the AI calculate the nutrition numbers?
What does one meal-plan generation produce?
Who is the system designed for?
Copy to discuss with AI
Challenge & re-estimate
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