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Client Case Study

PawsCLE

Dog daycare and boarding in Cleveland, OH. We built an AI scheduling tool that’s live today, and we’re developing a photo recognition system to automatically tag dogs in daycare photos.

pawscle.com

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AI product live

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Coming soon

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Scheduling time saved

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Dogs daily

Two problems. One solution live, one in development.

Each product tackles a specific pain point that was eating up hours of staff time every week.

BeforeManual Sorting

Staff scrolled through hundreds of daily photos trying to figure out which dogs were in each one. Parents wanted photos of their dogs, but with 50+ dogs onsite daily, manual matching just wasn't possible.

Time

2–4 hours/day

Cost

Staff time

AfterPawSnap AI (in development)

AI identifies individual dogs in every photo automatically. Each dog is enrolled with a few reference photos, then the model recognizes them going forward. Parents only see photos of their dogs.

Time

Automatic

Cost

Monthly + usage

In progress
Identifies individual dogs, not just breeds
In Development

PawSnap: AI dog photo tagging

An iOS app and cloud AI pipeline designed to recognize individual dogs in daycare photos and send the right photos to the right parents. Currently in development — not yet deployed.

Easy enrollment

Staff will take a few photos of each new dog through the app. The AI uses those to learn to recognize them going forward.

Batch photo processing

Designed to process an entire day of photos at once, identifying which dogs appear in each one automatically.

Built to scale

The ML model runs on Google Cloud — designed to scale up during busy periods and cost nothing when idle.

Happy parents

The goal: parents receive photos of their specific dogs automatically. No more scrolling through hundreds of unrelated images.

How it will work: Staff enrolls dogs with a few reference photos in the iOS app. Photos upload to Google Cloud Storage, where a YOLO ML model identifies individual dogs. Results will flow to a web dashboard for staff and directly to parents in the app.

Live

PawsCLE Scheduler: smart shift planning

An AI scheduling tool that pulls availability from Sling, builds optimized weekly schedules, and lets the manager approve with one click.

Syncs with Sling

Pulls employee availability and shift preferences automatically from the scheduling system you already use.

AI-generated schedules

Takes into account room coverage, certifications, shift balance, and employee preferences to build the best schedule.

Review before publishing

The AI generates a draft. You review, make any changes, and publish. You're always in control.

Prevents mistakes

Catches double-bookings, gaps in coverage, and scheduling conflicts before they become a problem.

How it works: The tool syncs with Sling to get who's available. AI considers room coverage needs, certifications, and preferences, then generates a draft schedule. The manager reviews it, tweaks anything they want, and publishes. Human judgment stays in the loop.

What we used to build it

PawSnap iOS

  • SwiftUI
  • Camera + Photos
  • YOLO ML Model
  • XcodeGen

PawSnap Web

  • Next.js
  • React
  • TypeScript
  • Tailwind CSS

PawSnap Backend

  • Firebase
  • Google Cloud Run
  • Docker
  • Cloud Storage

Scheduler UI

  • Vanilla JavaScript
  • Responsive grid layout
  • LocalStorage for drafts

Scheduler Backend

  • Node.js
  • Sling Workforce API
  • CORS proxy

Scheduler AI

  • Google Gemini
  • Structured JSON output
  • Constraint-aware prompts

Running a business with manual processes?

We'd love to hear about the tasks eating up your team's time.

PawsCLE Scheduler is live. PawSnap photo recognition is in development and not yet deployed. Results for the scheduler are based on initial deployment. Shared with permission.