Section 03: Technical Feasibility & Architecture
MeetingMeter - Meeting Cost Calculator
ASSESSMENT Technical Achievability Score
MeetingMeter relies on well-documented, mature APIs (Google Calendar, Microsoft Graph) and standard CRUD operations. The core logic—cost calculation—is deterministic arithmetic rather than probabilistic AI, reducing complexity. There is clear precedent for calendar analytics tools (Clockwise, Reclaim), proving the technical viability. The primary technical challenge is not "if" it can be built, but handling permission scopes and data privacy securely.
No major blockers exist. The score is not 10 because mapping unstructured email addresses to specific organizational cost centers (HRIS integration) can be complex depending on the customer's data hygiene.
Recommended Technology Stack
| Layer | Technology | Rationale |
|---|---|---|
| Frontend | Next.js 14 + Tailwind CSS + shadcn/ui | Next.js provides SSR for marketing pages and API routes for backend logic in a single repo. Tailwind/shadcn offers rapid, professional UI development without a dedicated designer. |
| Backend | Node.js (Next.js API) + Prisma ORM | JavaScript end-to-end allows a solo founder to move fast. Prisma provides type-safe database access, crucial for handling complex relational data (Orgs -> Users -> Meetings). |
| Database | PostgreSQL (Supabase) | SQL is required for complex analytics queries (aggregating costs by time periods). Supabase handles Auth, Realtime, and Postgres hosting, reducing DevOps overhead. |
| AI/ML Layer | OpenAI GPT-4o-mini (via Vercel SDK) | "Mini" models are sufficient for text classification (meeting types) and summarization. They offer near-instant latency at 1/10th the cost of standard models, preserving unit economics. |
| Infrastructure | Vercel + Supabase | Vercel offers industry-leading developer experience and preview deployments. The combination scales effortlessly from MVP to 10k+ users without managing servers. |
System Architecture
Feature Implementation Complexity
| Feature | Complexity | Effort | Dependencies |
|---|---|---|---|
| Calendar Integration (OAuth + Sync) | Medium | 5-7 days | Google/MS APIs, Webhooks |
| User Authentication & Roles | Low | 1-2 days | Supabase Auth |
| Cost Calculation Engine | Low | 2-3 days | Salary Data, Event Data |
| Analytics Dashboard (Charts) | Low | 3-4 days | Recharts/Tremor, Aggregation Queries |
| Organization Hierarchy Mapping | High | 7-10 days | HRIS API (optional), CSV Import |
| AI Insight Generation | Medium | 4-5 days | OpenAI API, Prompt Engineering |
| Calendar Nudge Injection | Medium | 3-4 days | Google/MS API Write Scopes |
AI/ML Implementation Strategy
Use Cases
- Meeting Classification: Analyze titles/descriptions to tag "Brainstorm" vs. "Status Update" vs. "Decision".
- Optimization Suggestions: Generate natural language tips like "Consider removing [Name] for this status update."
- Summarization: Create weekly "Meeting Spend" summaries for executives.
Model Selection & Cost
Primary: OpenAI GPT-4o-mini.
Rationale: Extremely fast (~200ms) and cheap ($0.15 / 1M tokens). Sufficient for classification and short text generation.
Estimated Cost: < $0.05 per user/month (assuming 1 AI call per meeting).
Quality Control & Hallucination Mitigation
Because the output is cost-critical, we use Structured Outputs (JSON mode) to force the AI to return specific data types (e.g., "efficiency_score": 1-10). We validate JSON schemas before saving to the DB. Human-in-the-loop is not required for individual calculations but is used for "Company-wide" insights.
Data Requirements & Strategy
Data Sources
- Primary: Google Calendar / Outlook API (Events, Attendees, Recurrence).
- Secondary: HRIS Import (Workday, BambooHR) or CSV for Salary/Role data.
- Fallback: User self-reported role/salary or industry benchmarks.
Schema Overview
Organizations → Users → CalendarEvents → Attendees.
SalaryBands table links Users to cost rates without storing individual salaries explicitly (optional privacy layer).
Privacy & Compliance
- PII: Email addresses and names are encrypted at rest (Postgres pgcrypto).
- GDPR: "Right to be forgotten" triggers deletion of all calendar history and user records.
- Salaries: Never displayed in raw form to other users; only used for aggregate calculations.
Third-Party Integrations
| Service | Purpose | Complexity | Cost | Criticality |
|---|---|---|---|---|
| Google Calendar API | Event sync & write | Medium (OAuth 2.0) | Free (Generous quota) | Must-have |
| Microsoft Graph API | Outlook/Teams sync | High (Complex OAuth) | Free (Low usage) | Must-have |
| Stripe | Payments & Billing | Medium | 2.9% + 30¢ | Must-have |
| Resend / SendGrid | Weekly Reports & Nudges | Low | Free tier → $20/mo | Nice-to-have |
| OpenAI API | Insights & Classification | Low | Usage-based (~$50/mo) | Future |
Scalability Analysis
Performance Targets
- Dashboard Load: < 1s (cached aggregation).
- Calendar Sync: < 5s per user (background job).
- Concurrent Users: 1,000 (MVP) → 10,000 (Year 1).
Bottlenecks & Strategy
- API Rate Limits: Google/MS have strict limits.
Mitigation: Implement exponential backoff and queue-based sync (Vercel Cron or BullMQ). - DB Read Load: Analytics are query-heavy.
Mitigation: Materialized views for daily/weekly stats; Redis for session caching.
Security & Privacy Considerations
Auth
OAuth 2.0 flow via Supabase. Refresh tokens stored securely. Role-Based Access Control (RBAC) for Admin vs. Member views.
Data
Encryption at rest (AES-256) for salary fields. TLS 1.3 for all data in transit. PII hashed where possible.
API
Rate limiting (Vercel edge config). Input sanitization to prevent SQL injection. CORS restricted to app domain.
Technology Risks & Mitigations
Google or Microsoft could change API limits, breaking the sync for enterprise users.
Mitigation: Use official SDKs that handle throttling. Implement a robust queueing system (e.g., Trigger.dev) for sync jobs. Monitor API error rates via Sentry.
Accidental exposure of individual salaries to peers could cause HR disasters.
Mitigation: Strict Row-Level Security (RLS) policies in Supabase. Audit all API queries. Use role-based cost estimates instead of raw salaries where possible.
Difficulty migrating if pricing scales unfavorably or features change.
Mitigation: Use standard SQL (Postgres) to avoid proprietary DB features. Containerize the application logic (Docker) to allow moving to AWS/Railway if needed.
Development Timeline (12 Weeks)
Foundation (Weeks 1-3)
- Next.js + Supabase setup.
- Google Calendar OAuth integration.
- Database schema (Users, Events).
- Basic event ingestion pipeline.
Core Logic (Weeks 4-7)
- Salary band configuration UI.
- Cost calculation engine.
- Outlook/Microsoft Graph integration.
- Analytics dashboard (charts & tables).
Intelligence & Polish (Weeks 8-10)
- AI Insight integration (classification/suggestions).
- Organization hierarchy mapping.
- Nudge system (email + calendar description).
- Stripe payment integration.
Launch (Weeks 11-12)
- Security audit & permissions hardening.
- Error handling (Sentry setup).
- Landing page copy & SEO.
- Onboarding flow optimization.
Required Skills & Team Composition
Solo Founder Feasibility
A solo full-stack developer with React/Node experience can build the MVP. The use of managed services (Supabase, Vercel) significantly lowers DevOps overhead.
Estimated Effort: ~400-500 hours for MVP.
Ideal Team Composition
- 1 Full-Stack Engineer: Next.js, TypeScript, SQL.
- 1 Product/Founder: Handles UX design, marketing, and support.
- 1 Part-time Data Analyst (Contract): Helps refine the cost models and benchmarking algorithms.