Trail camera photo organizer for deer hunters

The idea

A serious deer hunter runs three to six cameras at 100 to 300 dollars each, then does the actual analysis by scrolling a 2,000-photo SD dump in Windows Explorer, most of it wind-triggered empties. The information they want is simple: which bucks are around, which camera sees them, and at what time of day. That answer is currently assembled by memory and squinting.

Cellular camera subscriptions at 10 to 15 dollars a month per camera prove hunters already pay recurring money for photo delivery, but that hardware upsell abandons everyone on cheap non-cellular cams. The wedge is serving exactly those people: bulk-upload the SD dump, let a vision model kill the empties and flag antlered deer, and turn named bucks into sighting timelines. Vision APIs got cheap enough for this to work at consumer pricing, which was not true two years ago.

Who pays

The buyer is the whitetail hunter with multiple non-cellular cameras, a demographic that demonstrably spends on gear and already tolerates per-month camera fees. Price at 8 dollars a month, seasonal churn expected and fine. Distribution through hunting forums, r/Hunting and r/bowhunting, and hunting YouTube channels who will demo it for a free season, with peak acquisition in the August to October scouting window.

MVP scope

• Bulk photo upload with EXIF parsing and per-camera organization
• Vision classification: empty, antlered deer, antlerless deer, other
• Named buck profiles with sighting history across cameras
• Best-stand-by-hour chart per camera with moon phase on each sighting
• Free tier at 250 photos, Stripe subscription at 8 dollars/month
• Skip for v1: automatic individual buck re-identification, video clips, cellular camera integrations, mapping/pins, sharing with hunting partners

Build StandData, a web app that organizes trail camera photos for deer hunters. Stack: Next.js, Claude API (vision) for classification, Supabase for auth/storage/database, Stripe for subscriptions.

Core flow: hunter creates named camera locations (e.g. North Ridge, Creek Bottom), then bulk-uploads an SD card dump of hundreds of JPEGs to a camera. On upload, parse EXIF for timestamp and camera model; where EXIF is missing, fall back to the timestamp burned into the image strip. Queue each photo through the Claude vision API with a prompt that classifies: empty frame, deer (antlered or antlerless), other animal, human/vehicle. Empties are hidden by default, not deleted. Antlered deer surface in a review queue where the hunter can assign the photo to a named buck (create Big Nine, attach sightings).

Pages: dashboard with recent activity per camera, upload page with drag-and-drop and progress per file, photo browser with filters (camera, date range, classification, named buck), buck profile page with a sighting timeline showing camera, date, time of day and moon phase (compute moon phase locally from the date, no API needed), and an insights page charting sightings by hour-of-day per camera to answer which stand to sit and when.

Implementation notes: process uploads through a Supabase Edge Function queue so a 900-photo dump does not block; store originals in Supabase Storage with a generated thumbnail. Batch vision calls and cache by file hash to avoid paying twice for duplicates.

Pricing: free up to 250 photos; 8 GBP/month unlimited.