an AI meal planner for home cooks
Estimated monthly cost at the usage scale below — billed by actual usage
3.89 req/s
Peak Concurrency
3.49 GB
Database Storage
0 GB
Object Storage
0 GB
Outbound data transfer
What is this app
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, and food preferences or restrictions, and the app generates a three-day plan with nine meals plus a consolidated shopping list in grams. Meal calories and macronutrients are sourced through real lookups against the USDA food nutrition database rather than estimated by AI.
As an anonymous visitor, I can view what the AI meal planner does for home cooks
As a home cook, I can enter my body statistics, activity level, goal, food preferences, and restrictions
As a home cook, I can generate and save a three-day meal plan with nine meals
As a home cook, I can review each meal's USDA-backed calories and macronutrients
As a home cook, I can view a consolidated shopping list with ingredient quantities in grams
50000
home_cooks
Registered people in the United States who cook meals at home and use the planner to create personalized meal plans and shopping lists.
0
anonymous_visitors
Unregistered visitors who can view the public product introduction but do not use personalized planning features until they register.
Requirements to minimum viable plan to cost
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 lookup and meal-generation workflows require multiple integrations, while the external consumer app needs ongoing publishing and professional branding; the current selection is based on the requirement for at least the BASIC plan.
See the capability-by-capability assessment ▾
PROJECT DEMAND
ALLOWANCE PROVIDED (COMPOSITION)
Basic
Basic is the minimum viable plan
Basic
(Plan tier: BASIC)
See minimum viable plan above
39
single-tenant kit
4 req/s
not purchased
(plan/kit 5 req/s)
Covered by plan/kit (margin ~25%)
0
Database storage add-on
3.74 GB
10GB × 1/year, amortized monthly
(plan/kit 200.00 MB + add-on +3.54 GB)
Add-on fills +3.54 GB gap beyond plan/kit
8.33
Object storage
add-on
0 B
not purchased
(plan/kit 2.00 GB)
No requirement
0
Outbound data transfer add-on
0 B/mo
not purchased
(plan/kit 2.00 GB/mo)
No requirement
0
AI points add-on
383.1M points
6,000,000 AI Points × 64/month
(plan/kit 385.0M points + add-on +382.1M points)
Add-on fills +382.1M points gap beyond plan/kit
640
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.
2 × t4g.large × 730h
EC2 t4g.large → 98.11
2 × db.m6g.large (Multi-AZ) × 730h
RDS PostgreSQL db.m6g.large → 232.14
3.74 GB-month
RDS gp3 storage → 0.43
0.00 GB-month
S3 Standard → 0
0.00 GB (first 100GB free)
Internet egress → 0
Total ≈ $330.68 / mo
Pure cloud resources
DEVELOPMENT COST
MONTHLY CLOUD INFRA ($/MO)
MONTHLY TOTAL
(INFRA + OPS)
Traditional outsourcing / build in-house
about $140,000 - $190,000
≈ $331
Based on the AWS estimate above
≈ $2,331
Infra $331 + ops ~$2,000
4-6 months
5 / 5
Vibe Coding
about $18,000 - $26,000
≈ $331
Based on the AWS estimate above
≈ $1,831
Infra $331 + ops ~$1,500
hours
5 / 5
AI full-stack generation
about $7,000 - $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 ≈ $441/mo at AWS list prices, often more), plus the extra dev and ops staff. Momen bundles all of it into $368/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 gives no explicit user count or directly implied business scale. This is the standard planning assumption for an unspecified SaaS audience and can be adjusted when expected registration or market data is available.
We assume 225 equivalent running days because this is a standard consumer SaaS product expected to grow progressively rather than launch with a full pre-existing dataset or remain at a short recent burst. If the product launches with an established user base or experiences a rapid one-time adoption surge, this parameter can be adjusted.
Routine Results Review
Routine Results Review
Routine Plan Generation
30
times/month
3.89 req/s
Peak load
We assume saved-result review is a separate daily scenario because it produces read activity even when no new plan is generated. Registered home cooks may inspect meal nutrition and shopping quantities during an evening or preparation period, and these reads should not be blended into the generation purpose because their core action and database behavior differ. The duration represents a two-hour review period, and the monthly frequency reflects daily recurrence. The two purposes distinguish meal-detail review from shopping-list review while retaining the exact flow action chain declared in the blueprint.
Main impact: Peak Concurrency
The scenarios above set the assumptions for each resource; below is the full calculation based on those assumptions. 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.
Public browsing flow for visitors learning what the meal planner does.
Primary registered-user flow for creating and reviewing a personalized three-day meal plan.
page
data_table
ai_agent
action_flow
Home Page
Public introduction page explaining the meal planner for home cooks.
Planner Form Page
Input form where registered home cooks provide the information used to generate a personalized three-day plan.
Meal Plan Results Page
Results page showing the generated nine-meal plan, nutrition values, and consolidated shopping list.
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 primarily affect resource usage?
Why is plan generation more involved than a basic form submission?
How are calories and macros calculated?
How does the shopping list work?
Who is the application intended for?
Copy to discuss with AI
Challenge & re-estimate