Original Idea
Appointment Slot Optimizer A background service that learns demand patterns and auto-fills gaps with waitlist offers and smart buffers.
Product Requirements Document: SlotOptim Engine (v1.0)
1. Executive Summary
The SlotOptim Engine is an intelligent background service designed to eliminate the "Swiss cheese effect" in professional calendars. By leveraging real-time calendar fragment analysis and machine learning, the system identifies underutilized time gaps and automatically orchestrates waitlist notifications to fill them. It maximizes revenue for service-based businesses (medical, legal, wellness) by converting fragmented downtime into billable appointments while dynamically managing buffers to prevent staff burnout.
2. Problem Statement
Service-based businesses lose 15–25% of potential revenue due to:
- Fragmented Gaps: Small, unbookable 15–45 minute slivers between appointments.
- Manual Latency: Staff cannot react fast enough to fill a last-minute cancellation.
- Static Buffers: Uniform rest periods that don't account for service complexity or predicted delays, leading to cascading schedule drift.
- Unmanaged Waitlists: Static lists that require manual phone calls, which customers often miss.
3. Goals & Success Metrics
- Increase Calendar Utilization: Target a 12% increase in billable hours per provider.
- Reduce Gap Response Time: Move from manual notification (hours) to automated "Flash Slot" offers (seconds).
- Revenue Recovery: Track total dollar value of slots filled via the Optimizer.
- User Retention: Achieve <5% churn by proving ROI via a Revenue Recovery Dashboard.
4. User Personas
- Dr. Sarah (Medical Practice Manager): Needs to keep 4 doctors' schedules full. Overwhelmed by cancellations and HIPAA compliance requirements.
- James (High-end Salon Owner): Focused on maximizing "chair time" and offering a premium, tech-forward experience to clients.
- Alex (The Waitlisted Customer): Wants an earlier appointment but doesn't want to call back repeatedly. Values "first-come, first-served" transparency.
5. User Stories
- As a Practice Manager, I want the system to detect a 45-minute gap so that it can automatically offer it to the top 5 qualified waitlisted patients.
- As a Provider, I want "Smart Buffers" to increase after complex surgeries so that I don't run late for subsequent patients.
- As a Customer, I want to receive a WhatsApp link for a newly opened slot so I can book it instantly with one click.
- As a Business Owner, I want to see a heatmap of demand patterns so I can adjust my staff's working hours to match peak interest.
6. Functional Requirements
6.1. Real-time Gap Detection
- Analyze Google/Microsoft calendars using webhook-driven delta sync.
- Identify "Unproductive Gaps" (shorter than the minimum service time).
- Flag "High-Risk Slots" based on predictive no-show scoring.
6.2. Automated Waitlist Orchestration
- Flash Slot Logic: Trigger SMS/WhatsApp notifications to waitlisted users when a gap opens.
- Atomic Booking: Use Redis distributed locking to ensure "First-to-Click" wins without double-booking.
- Priority Weighting: Sort waitlist offers by customer loyalty, service value, or time-on-list.
6.3. Smart Buffer Management
- Dynamic adjustment of post-appointment "cooldown" periods.
- Service-aware buffers (e.g., +15 mins for new patients, +0 for follow-ups).
6.4. Predictive Analytics (ML)
- Predict no-show probability for every booking.
- Suggest "Overbooking" only when the aggregate risk score exceeds a safety threshold.
7. Technical Requirements
7.1. Core Tech Stack (2026 Standards)
- Backend: FastAPI (2026 Stable) utilizing Pydantic V2 (Rust Engine) and
uvloop. - Frontend: Next.js 15 (App Router) with React 19 and Tailwind CSS V4.
- Database: PostgreSQL 17+ with
btree_gistfor time-range indexing. - Real-time/Locking: Redis 7.4+ for Lua-based atomic locking.
- Identity: Auth0 (Okta) with Fine-Grained Authorization (FGA) for HIPAA/B2B isolation.
- Compute: AWS ECS Fargate on Graviton4 processors.
7.2. External Integrations
- Calendar: Google Calendar API (Incremental Sync) & Microsoft Graph API (Delta Queries).
- Communication: Twilio for SMS/WhatsApp via SQS-buffered workers.
- Payments: Stripe for "No-show protection" deposits.
8. Data Model
| Entity | Key Attributes | Relationships |
| :--- | :--- | :--- |
| Provider | id, org_id, timezone, min_gap_config | 1:N Appointments |
| Appointment | id, time_range (tstzrange), service_type, no_show_risk | M:1 Provider |
| WaitlistEntry | id, user_contact, preferred_ranges, priority | M:1 Org |
| SlotGap | id, start, end, status (Open/Filled/Expired) | 1:1 Triggering Cancellation |
9. API Specification (Highlights)
GET /v1/gaps/analyze
- Purpose: Force a scan for a specific provider's fragments.
- Response:
200 OKwithList[GapObject].
POST /v1/waitlist/offer
- Payload:
{ "gap_id": "uuid", "strategy": "priority_burst" } - Action: Triggers the Step Functions workflow to notify users.
POST /v1/bookings/instant-claim
- Payload:
{ "slot_token": "jwt", "customer_id": "id" } - Mechanism: Uses Redis
SETNXwith a 300s TTL to hold the slot during checkout.
10. UI/UX Requirements
- Operational Command Center: A Next.js dashboard using Container Queries (@container) to ensure widgets work in any layout.
- Capacity Heatmap: Recharts-based visualization of "Fragile Timespaces" (areas of high cancellation risk).
- Skeleton States: Mandatory use of React Suspense for all asynchronous data widgets.
11. Non-Functional Requirements
- Latency: Gap analysis must complete in <200ms using optimized interval arithmetic (NumPy/Polars).
- Concurrency: Support 10,000+ SMS notifications in a 60-second burst using AWS Step Functions Distributed Map.
- Compliance: SOC2 Type II and HIPAA-compliant data encryption at rest (AES-256) and in transit (TLS 1.3).
12. Out of Scope
- Building a full Electronic Medical Record (EMR) system.
- Handling physical room/equipment scheduling (V1 focuses on staff time only).
- Direct payroll processing.
13. Risks & Mitigations
- Risk: API Throttling from Google/Microsoft.
- Mitigation: Implement Push-Triggered Delta Sync with exponential backoff.
- Risk: Double-booking during high-traffic "Flash Slot" claims.
- Mitigation: Mandatory Redis Lua scripts for atomic "Check-and-Set" logic.
- Risk: SMS Fatigue.
- Mitigation: User-level "Quiet Hours" and frequency capping in the notification engine.
14. Implementation Tasks
Phase 1: Project Setup & Infrastructure
- [ ] Initialize FastAPI 2026 project with Pydantic V2 and
uvloop - [ ] Set up Next.js 15 (App Router) with Tailwind CSS V4 and
shadcn/ui - [ ] Configure Auth0 Organizations for multi-tenant identity management
- [ ] Provision AWS RDS (PostgreSQL 17) and enable
btree_gistextension
Phase 2: Calendar & Gap Logic
- [ ] Implement Google/Microsoft OAuth 2.0 flow with limited scopes
- [ ] Build the "Fragment Analysis" engine using Python
interlaplibrary - [ ] Create PostgreSQL
EXCLUDEconstraints to prevent overlapping time ranges - [ ] Implement Webhook handlers for Google
watchand MS Graphdelta
Phase 3: Waitlist & Atomic Booking
- [ ] Develop the Redis-based "Hold-then-Confirm" state machine
- [ ] Implement Lua scripts for atomic slot acquisition
- [ ] Set up AWS Step Functions Distributed Map for high-burst SMS triggers
- [ ] Build the "Instant Claim" deep-link landing page (React 19)
Phase 4: Machine Learning & Analytics
- [ ] Train XGBoost model for no-show prediction on anonymized historical data
- [ ] Integrate Meta's Prophet for weekly demand forecasting
- [ ] Build the "Revenue Recovery" dashboard with Recharts
- [ ] Implement SOCI (Seekable OCI) on ECS Fargate for sub-10s task scaling
Phase 5: Hardening & Compliance
- [ ] Conduct load testing (target: 20k RPS on gap detection)
- [ ] Implement HIPAA-compliant audit logging for all calendar modifications
- [ ] Finalize "Smart Buffer" logic with service-category weights
- [ ] Execute automated penetration testing on Auth0 FGA boundaries