🚲 bikeshopdesk Live · Self-host

Sales, repairs, parts, and inventory for local bike shops

New + used bike inventory. Parts lookup by make/model. Repair intake tickets (diagnosis, parts, labor, status). Customer history for repeat repair customers. Sales with financing-option routing. Trade-in credit management. For a 1-3 mechanic shop that'd rather focus on wrenching.

What it does

🚴

Bike inventory

New + used bikes with make/model/size/condition/price. Photo + spec sheet. Trade-in value auto-suggest from prior similar bikes sold.

🔧

Repair tickets

Customer drops off. Mechanic diagnoses. Parts + labor estimate for approval. Status track (waiting for parts, in-progress, ready). SMS customer at each stage.

⚙️

Parts catalog

Lookup by make/model/year. Compatible-parts suggestions. Supplier ordering with backorder tracking. Per-part margin visibility.

👤

Customer history

Repeat customers see their prior bike + repair history. Tune-up reminder emails. Loyalty discount after N repairs.

💳

Sales + trade-ins

POS for bikes + accessories + apparel. Financing lookup (affirm/klarna). Trade-in credit against new purchase. Daily close-out.

🔒

Shop-owned

Flask + SQLite. Your customer + repair history stays on your server. Not a corporate-bike-shop SaaS.

Quickstart

# clone and install git clone https://github.com/Dangercorn-Enterprises/bikeshopdesk.git cd bikeshopdesk pip install -r requirements.txt # run python app.py

Pricing

Self-host
$0/forever
  • Clone from GitHub
  • Run on any laptop or VPS
  • Your data stays yours
  • All core features
  • AI features (BYOK)
Get the source
Multi-shop
$149/mo
  • Everything in Pro
  • Multi-shop accounts
  • Strava integration for customer mileage
  • Bike-fit assessment module
  • SSO
  • Priority support
Contact sales

Hosted plans are early-access. Self-host today; email tim@dangercorn.net to join the waitlist.

Related products

bikeshopdesk is one of 220+ verticals scaffolded from the same template. Each gets a working skeleton for free; individual ones get promoted to full products as demand surfaces.