Using
full-stack no-code platform · Momen
to build
a Bay Area junk-removal request platform
how much does it cost?
~
$529
/ mo
Estimated monthly cost at the usage scale below — billed by actual usage
1.00 req/s
Peak Concurrency
1.76 GB
Database Storage
80.75 GB
Object Storage
99.08 GB
Outbound data transfer
Start Building for Free
Estimate a new idea
PROJECT OVERVIEW
What is this app
BayHaul Junk Removal is an online request platform for a Bay Area junk hauling company. Customers describe their junk and upload photos, then receive an AI-generated price range and structured list of detected items before choosing a pickup date, one of nine fixed one-hour slots, and an address. The system calculates warehouse-to-customer driving distance and time, while BayHaul staff review requests, accept or decline them with optional notes, and allow declined requests to be edited and resubmitted.
As an anonymous visitor, I can learn about BayHaul's online junk-removal service and start a request
As a customer, I can describe my junk and upload photos to receive a price range and detected-item list
As a customer, I can confirm a pickup date, one of nine fixed one-hour slots, and an address so the request receives route details
As a customer, I can review a declined request, edit it, and resubmit it for a recalculated quote and route
As a staff member, I can review customer requests, uploaded photos, detected items, and warehouse-to-customer route details
As a staff member, I can accept or decline a request and optionally record a note
0
anonymous_visitors
Public visitors who can learn about BayHaul and enter the online request journey without a registered account.
47000
customers
Registered customers who describe junk, upload photos, receive AI-assisted quote information, schedule pickup details, and resubmit declined requests.
3000
staff_members
BayHaul team members who review incoming requests and accept or decline them with optional notes.
COST BREAKDOWN
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
Multiple integrations and ongoing public service require at least BASIC.
See the capability-by-capability assessment ▾
ITEM_NAME
PROJECT DEMAND
ALLOWANCE PROVIDED (COMPOSITION)
COVERAGE
AMOUNT
Basic
Basic is the minimum viable plan
Basic
(Plan tier: BASIC)
See minimum viable plan above
39
single-tenant kit
1 req/s
not purchased
(plan/kit 5 req/s)
Covered by plan/kit (margin ~400%)
0
Database storage add-on
1.89 GB
10GB × 1/year, amortized monthly
(plan/kit 200.00 MB + add-on +1.69 GB)
Add-on fills +1.69 GB gap beyond plan/kit
8.33
Object storage add-on
86.70 GB
100GB × 1/year, amortized monthly
(plan/kit 2.00 GB + add-on +84.70 GB)
Add-on fills +84.70 GB gap beyond plan/kit
2.92
Outbound data transfer add-on
106.38 GB/mo
500GB × 3/year, amortized monthly
(plan/kit 2.00 GB/mo + add-on +104.38 GB/mo)
Add-on fills +104.38 GB/mo gap beyond plan/kit
8.75
AI points add-on
281.2M points
6,000,000 AI Points × 47/month
(plan/kit 283.0M points + add-on +280.2M points)
Add-on fills +280.2M points gap beyond plan/kit
470
Monthly total
plan + add-ons · usage-based · no development cost
$529
/ mo
WHY MOMEN
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.
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
1.89 GB-month
RDS gp3 storage → 0.22
86.70 GB-month
S3 Standard → 1.99
0.00 GB (first 100GB free)
Internet egress → 0
Total ≈ $332.46 / mo
Pure cloud resources
ROUTE
DEVELOPMENT COST
MONTHLY CLOUD INFRA ($/MO)
MONTHLY TOTAL (INFRA + OPS)
TIME TO LAUNCH
CUSTOMIZATION
Traditional outsourcing / build in-house
about $120,000 - $170,000
≈ $332
Based on the AWS estimate above
≈ $2,332
Infra $332 + ops ~$2,000
4-6 months
5 / 5
Vibe Coding
about $14,000 - $22,000
≈ $332
Based on the AWS estimate above
≈ $1,832
Infra $332 + ops ~$1,500
hours
5 / 5
AI full-stack generation
about $6,000 - $10,000
≈ $332
Based on the AWS estimate above
≈ $1,832
Infra $332 + 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
$59
All-in: egress / storage / auto-scaling; excludes AI usage
$59
hours
5 / 5
Infrastructure cost is unavoidable
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.
Vibe-coding speed + a production-grade backend
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.
SCALE & SIZING
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.
50000
Total users
We assume 50000 registered accounts because the project description gives no explicit customer, staff, or market scale. This remains the standard planning assumption for an unspecified public-facing service and can be adjusted when BayHaul provides its expected account population.
225
Data retention period
We assume 225 equivalent running days because this is a standard linear-growth service-request platform that builds usage gradually rather than launching with a full pre-existing dataset or experiencing a short recent burst. If BayHaul migrates a large historical request archive or launches after a concentrated campaign, this parameter can be adjusted accordingly.
Core business scenarios
Customer Request Operations
Customer Request Operations
Customer Request Operations
Customer Request Operations
Customer Request Operations
30
times/month
1 req/s
Peak load
We assume customer activity is a weakly assembled daily pattern spread across daytime and evening rather than a mandatory synchronized burst. The scene contains three separate purposes: new quote submission and scheduling, status review, and declined-request resubmission. They are separated because each has a different business intent and write profile, even though they can happen during the same customer-service period. The duration is a 14,400-second daily window and the monthly frequency is approximately 30 occurrences because customers can use the platform every day.
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.
Peak Concurrency
1.00 req/s
Database Storage
1.76 GB
Object Storage
80.75 GB
Outbound data transfer
99.08 GB
AI Points
281M AI Points
DEVELOPMENT SCOPE
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_visitors
browse_service_and_start
Public browsing flow for learning about BayHaul and starting an online request.
page
customers
submit_and_schedule_request
End-to-end customer flow from junk description through AI quote review and pickup scheduling.
page
data_table
ai_agent
action_flow
customers
review_request_status
Customer flow for checking request status and reviewing a specific request.
page
data_table
customers
edit_and_resubmit_request
Customer correction and resubmission flow for a declined request.
page
data_table
ai_agent
action_flow
staff_members
staff_review_queue
Staff operational review flow for inspecting incoming requests and route information.
page
data_table
staff_members
staff_decide_request
Staff accept-or-decline flow with an optional note.
page
data_table
page
data_table
ai_agent
action_flow
Home Page
Public entry page explaining BayHaul's online junk-removal request service.
Quote Request Page
Customer form for describing junk, uploading photos, and submitting an AI quote request.
Quote Review Page
Customer page for reviewing the quote and confirming pickup scheduling details.
Request Status Page
Customer area for reviewing request outcomes and resubmitting declined requests.
Staff Request Dashboard
Staff queue and detail workspace for reviewing customer requests and route information.
Staff Decision Page
Staff decision form for accepting or declining a request with an optional note.
FAQ
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 drive this project's resource usage most?
How do uploaded junk photos affect the estimate?
When is the AI agent used?
When are geocoding and routing APIs called?
How are the nine pickup time slots represented?
Copy to discuss with AI
Challenge & re-estimate