Doastly is a modern pet grooming platform that streamlines salon operations and enhances customer experience with real-time updates, automated reminders, and secure payments. Salons can manage bookings, share grooming reports, and track insights, while pet owners enjoy greater transparency and reduced kennel time.
The Problem
Doastly originally focused on in-store grooming services, offering robust tools for salon scheduling and communication. As customer demand shifted toward convenience and at-home care, the team set out to launch a mobile grooming solution. This transition introduced a new layer of complexity, requiring the platform to adapt to dynamic, on-the-go workflows and real-time logistics.
User Pain Points
- Booking remained semi-manual, lacking smart time slot suggestions based on location and availability.
- Users had no visibility into groomer location or arrival time, leading to uncertainty and missed handoffs.
Business Challenges
- Optimizing daily routes for mobile groomers across large service areas required real-time, AI-powered logistics.
- No-shows and last-minute cancellations disrupted schedules and reduced efficiency.
- Lack of predictive tools made it hard to scale operations or assign appointments based on traffic or pet behavior patterns.
- The system needed to support role-based access and mobile responsiveness for groomers working in the field.
The AI-Powered Solution
We identified four practical AI solutions tailored to optimize the Doastly experience, enhancing user satisfaction and operational efficiency.
AI-Optimized Scheduling
AI suggests optimal time slots based on user location, groomer availability, and historical behavior—helping reduce double bookings and improving efficiency.
Route Optimization
Leverages real-time traffic data and Vehicle Routing Problem (VRP) algorithms to generate efficient routes for mobile groomers with multiple stops.
Grooming Recommendations
AI analyzes uploaded pet images and historical grooming data to recommend personalized services based on breed, coat type, and care patterns.
Virtual AI Assistant
Handles grooming-related queries, sends predictive reminders, shares live ETAs, and gathers user feedback, all through a friendly AI chatbot experience.
Competitive Analysis: Uber's Route Optimization
Uber has set a global benchmark in real-time, AI-powered route optimization. Their approach inspired the Doastly team to adopt similar logic tailored for mobile pet grooming. By studying Uber’s logistics playbook, we identified techniques to improve accuracy, reduce downtime, and scale efficiently for salon owners and independent groomers alike.
- Real-Time Data: Uber integrates GPS, live traffic, and historical data for adaptive routing — a model we mirrored to optimize daily grooming stops.
- DeepETA: Their deep learning model for ETA predictions influenced our predictive grooming time estimates and ETA buffers.
- Graph Algorithms: Uber uses Dijkstra and A* pathfinding; we combined these with Vehicle Routing Problem (VRP) solvers for complex multi-stop planning.
- Dynamic Re-Routing: Uber continuously adjusts routes — we implemented similar logic to respond to traffic delays or grooming time deviations in real-time.
- Applied to Doastly: These strategies now power our route generation engine, groomer dashboards, and client-facing updates for transparency and trust.
Results & Impact
- Booking time reduced by 40% through AI scheduling.
- Groomer travel efficiency improved by 30% with optimized routing.
- User satisfaction increased from 3.8 to 4.6 through personalization and real-time updates.
Key Takeaways
- AI enhances UX while keeping experiences seamless and intuitive.
- Dynamic route optimization improves time management and productivity.
- Personalized grooming recommendations foster stronger pet-parent trust.
User Flow: AI-Optimized Mobile Grooming
Step 1: Dashboard Overview
- Start Point: The user launches the Doastly app and lands on the main dashboard.
- Interactive Calendar: A 15-day horizontally scrolling calendar is displayed.
- Current Day Highlighted: The current date is clearly marked, showcasing the total number of appointments and a map icon for quick navigation.
- Action: The user taps on the highlighted date to proceed.
Step 2: AI Route Suggestion
- Automatic Optimization: Doastly’s AI instantly calculates the best route for the selected day.
- Factors Considered: The route is optimized based on grooming history, location clusters of appointments, and live traffic data.
- Visual Guidance: A map appears, displaying the optimized route with a list of all scheduled appointments.
- User Control: The user can review the route before moving forward.
Step 3: Interactive Route Map
- Visual Navigation: The user accesses a detailed route map with clickable pins for each grooming stop.
- Grooming Actions:
- Start Grooming: The user taps “Check-In” on a pet’s pin, initiating the grooming process.
- Modify Route: Users can remove a grooming request if needed.
- Complete Grooming: After grooming, the user can complete the payment process.
Step 4: Return to Map + Live Tracking
- Return to Map: Once a grooming session is completed, the app automatically redirects back to the map view.
- Real-Time Updates: The map dynamically shows the status of completed and upcoming stops.
- Live ETA: Users can see updated arrival times for the remaining stops, and receive real-time notifications.
Mockups: AI-Optimized Mobile Grooming
Dashboard Mockup
AI Route Map
High-Level Solution Overview: Role-Based Access & AI-Powered Scheduling
Salon Owner Workflow
Salon owners assign groomers to appointments via the backend. Once assigned, groomers are automatically linked—no manual steps required in the app.
Groomer Access (Mobile App)
- View optimized daily routes
- Check in/out of appointments
- Process payments
- Receive AI-based rescheduling suggestions
This ensures a personalized and efficient grooming workflow with minimal coordination.
Pet Owner Notifications (In Progress)
- Get notified when the groomer is en route
- Receive alerts when grooming starts/ends
- Track session updates via app
Future Feature: Live Route Tracking
In the next phase, pet owners will be able to track their groomer's location in real-time—similar to Uber or DoorDash. This will improve trust, reduce no-shows, and enhance the overall experience.
AI Integration Using Pre-Trained APIs & Agents
AI-Driven Enhancements in Route Optimization
-
Smart Route Generation: AI clusters appointments by location and calculates the most time-efficient order using optimization algorithms (e.g., Traveling Salesman Problem or VRP).
Value: Reduces fuel use and increases grooming capacity per day. -
ETA Adjustment with Real-Time Traffic: Google Maps Traffic data feeds into the AI model to dynamically adjust estimated times of arrival.
Value: Increases reliability, reduces customer wait time and missed appointments. -
Rescheduling Logic: When traffic is severe or grooming times shift, AI proactively recommends rescheduling and offers new time slots.
Value: Maintains service quality and reduces pressure on the groomer. -
Historical Grooming Time Analysis: AI uses past grooming durations to predict and adjust future appointment timing.
Value: Enhances time prediction accuracy and reduces overbooking. -
Explainable Routing for Transparency: OpenAI agents or logic layers provide clear reasoning behind suggested routes (e.g., "Why this route?").
Value: Builds user trust and confidence, especially for unexpected paths.
Technology
- Google Maps APIs (Directions, Distance Matrix, Traffic)
- Angular Google Maps (`@agm/core`)
- OpenAI Function Calling or Agent APIs
- Firebase / Firestore for session management
- Optional: D3.js or Chart.js for ETA visualizations
Click each title to view more details.
AI-Optimized Scheduling
Goal: Suggest smart appointment time slots based on user location, groomer availability, and history.
- Core Logic: Angular with rules (availability, zone)
- AI Layer: OpenAI Function Calling
- Location Input: Google Maps Geolocation API
- Calendar: Firebase / Firestore
Grooming Recommendations
Goal: Analyze pet photos and suggest grooming packages based on breed, coat type, and history.
- Image Upload: Ionic File Upload or Capacitor Camera Plugin
- Detection: Google Cloud Vision API or Roboflow
- Logic: Custom Angular Service
- Advanced: GPT-4 Vision for detailed suggestions
Virtual AI Assistant
Goal: Provide an in-app chatbot for grooming support, reminders, and automated responses.
- Chatbot Framework: Dialogflow ES/CX or OpenAI GPT-4 + LangChain
- UI Integration: Angular Component or iframe Widget
- Reminders: Firebase Cloud Messaging
- Memory: Firebase Firestore or session-based storage
Sentiment Analysis
Goal: Automatically assess feedback and flag unhappy users for follow-up.
- Collection: Angular Forms + Firebase Firestore
- Sentiment API: HuggingFace or OpenAI (text-davinci)
- Flagging: Admin dashboard alert
As Product Designer (with an Existing Design System)
As a Product Designer working on AI-driven features in Doastly, I was responsible for:
Experience Strategy
Define AI value across the grooming journey and map AI features to business goals.
User Flow Design
Design intuitive AI-assisted flows with fallback UX for AI uncertainty.
Prototyping & Testing
Build AI flows in Figma and validate with user testing.
AI Collaboration
Define AI prompts, input/output structure, and work with ML engineers on edge cases.
Design System Extension
Expand Doastly’s design system to include AI elements like suggestion chips, AI cards, and assistant UIs.
Key Deliverables:
Journey Mapping
Journey maps & user insights highlighting pain points and AI opportunity areas.
UX Artifacts
Flows, wireframes, and high-fidelity Figma screens using Doastly’s design system.
Dev Handoff
Developer-ready specs: prototypes, annotated screens, and AI prompt structures.
Summary of Impact:
“As a Product Designer, I spearheaded the strategy and execution of AI-driven features, seamlessly guiding them from research to production. I ensured each component aligned with our design system and consistently delivered measurable user impact.”