a Bay Area junk-removal request platform
Estimated monthly cost at the usage scale below — billed by actual usage
1.43 req/s
Peak Concurrency
3 GB
Database Storage
100.11 GB
Object Storage
108.47 GB
Outbound data transfer
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.
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
External branded service requires ongoing publishing, custom branding, and multiple integrations; 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
2 req/s
not purchased
(plan/kit 5 req/s)
Covered by plan/kit (margin ~150%)
0
Database storage add-on
3.23 GB
10GB × 1/year, amortized monthly
(plan/kit 200.00 MB + add-on +3.03 GB)
Add-on fills +3.03 GB gap beyond plan/kit
8.33
Object storage
add-on
107.49 GB
100GB × 2/year, amortized monthly
(plan/kit 2.00 GB + add-on +105.49 GB)
Add-on fills +105.49 GB gap beyond plan/kit
5.83
Outbound data transfer add-on
116.47 GB/mo
500GB × 3/year, amortized monthly
(plan/kit 2.00 GB/mo + add-on +114.47 GB/mo)
Add-on fills +114.47 GB/mo gap beyond plan/kit
8.75
AI points add-on
353.4M points
6,000,000 AI Points × 59/month
(plan/kit 355.0M points + add-on +352.4M points)
Add-on fills +352.4M points gap beyond plan/kit
590
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
3.23 GB-month
RDS gp3 storage → 0.37
107.49 GB-month
S3 Standard → 2.47
8.47 GB (first 100GB free)
Internet egress → 0.76
Total ≈ $333.86 / mo
Pure cloud resources
DEVELOPMENT COST
MONTHLY CLOUD INFRA ($/MO)
MONTHLY TOTAL
(INFRA + OPS)
Traditional outsourcing / build in-house
about $120,000 - $180,000
≈ $334
Based on the AWS estimate above
≈ $2,334
Infra $334 + ops ~$2,000
4-6 months
5 / 5
Vibe Coding
about $18,000 - $26,000
≈ $334
Based on the AWS estimate above
≈ $1,834
Infra $334 + ops ~$1,500
hours
5 / 5
AI full-stack generation
about $8,000 - $11,000
≈ $334
Based on the AWS estimate above
≈ $1,834
Infra $334 + 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
$62
All-in: egress / storage / auto-scaling; excludes AI usage
$62
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 customer, staff, or market scale. This is the standard planning assumption for an unspecified public-facing service and can be adjusted when BayHaul provides its expected account population.
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 marketing campaign, this parameter can be adjusted accordingly.
Daily Public Browsing
Customer Follow-up Window
Daily Public Browsing
Routine Customer Requesting
Routine Customer Requesting
30
times/month
1.43 req/s
Peak load
We assume public service discovery occurs throughout a normal day rather than in a synchronized burst, so it is modeled as a broad daily scenario. The scenario contains one purpose because public information viewing is distinct from logged-in request submission and staff operations. A 14-hour active window represents daytime and evening customer discovery, and the monthly frequency is daily because the public website remains available 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.
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 learning about BayHaul and starting an online request.
End-to-end customer flow from junk description through AI quote review and pickup scheduling.
Customer flow for checking request status and reviewing a specific request.
Customer correction and resubmission flow for a declined junk-removal request.
Staff operational review flow for inspecting incoming requests and route information.
Staff accept-or-decline flow with an optional note.
page
data_table
ai_agent
action_flow
Home Page
Public entry page explaining the online junk-removal request service and directing visitors to begin a quote.
Quote Request Page
Customer form for describing the junk, uploading photos, and submitting the request for an AI-generated quote and detected-item list.
Quote Review Page
Customer review and scheduling page for accepting the quote and supplying pickup details.
Request Status Page
Customer area for reviewing request outcomes and resubmitting declined requests with revised information.
Staff Request Dashboard
Staff queue and detail workspace for reviewing customer requests and the operational route information.
Staff Decision Page
Staff decision form for accepting or declining a request and recording an optional note.
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