plan-generalPurposeSaas

Prompt file imported from BeathovenGala/NexaAssist (.github/prompts/plan-generalPurposeSaas.prompt.md). Copyright stays with the author.

Plan: General-Purpose SaaS (appointments, inventory, chatbot, ads)

TL;DR - Build a multi-tenant SaaS platform that supports role-based user access, calendar/appointment booking, inventory management, a chatbot that queries inventory and books appointments, and automated ad/poster generation and delivery (e.g., WhatsApp). Start with a focused MVP for hospitals/medical stores then generalize for grocery / fashion.

Steps

1. Discovery & Constraints (short): confirm compliance needs (HIPAA/PHI for hospitals), scale targets, and initial client personas. blocks: legal/compliance decisions
2. Choose tech stack and infra (quick decision): pick frontend, backend, DB, queue, LLM+image APIs, notification providers.
3. Initialize repo & scaffolding: monorepo or separated repos; create frontend/, backend/, infra/, docs/, tests/.
4. Core platform services (auth, tenancy, RBAC): implement JWT/OAuth, tenant isolation, role model, audit logging. depends on step 2
5. MVP features (parallel where possible):
   • Appointment booking & calendar UI + API
   • Basic inventory CRUD and availability query
   • Chatbot integration (LLM + inventory lookup hooks)
   • Notifications (email/SMS/WhatsApp) + webhook delivery
6. Admin features: schedules management, inventory adjustments, offer/campaign composer
7. Ads/image generation integration: image generation API + template system + send via WhatsApp API
8. Background processing: job queue for notifications, image generation, async chat fallbacks
9. Testing & QA: unit, integration, E2E, security scans, compliance checks
10. Deploy: CI/CD pipelines, staging, production, monitoring, backups

Relevant files to create initially

• frontend/ — React + Next.js app skeleton
• backend/ — Node.js (NestJS/Express) or Python (FastAPI) service
• infra/ — docker-compose.yml, basic Terraform/CloudFormation
• README.md, .env.sample, package.json or requirements.txt

Tech stack (recommended)

• Frontend: React + Next.js, TypeScript, Tailwind CSS
• Backend: Node.js + NestJS (or FastAPI) with TypeScript (or Python)
• DB: PostgreSQL (multi-tenant via schema or row-level), Redis for caching
• Jobs/Queue: BullMQ + Redis
• Storage: S3-compatible (AWS S3)
• Auth: Auth0 or OpenID Connect + JWTs
• LLM / Chatbot: OpenAI (gpt-4o/advanced) or Anthropic; local LLM for on-prem optional
• Image generation: OpenAI images / Stability.ai / Midjourney API
• Messaging/WhatsApp: Twilio or WhatsApp Business Cloud API
• Infra: Docker, Kubernetes (optional), Terraform
• Monitoring: Prometheus + Grafana / Sentry

Users & Roles (RBAC)

• Super Admin: platform-wide config, billing
• Tenant Admin (store/hospital owner): manage org, users, inventory, campaigns
• Manager: manage schedule, inventory approvals, messages
• Doctor / Staff / Pharmacist: view appointments, inventory, communicate with users via chat
• Customer / Patient / Shopper: book appointments, chat, view offers
• Chatbot: service account used by LLM integrations

Data model (high level tables / collections)

• organizations: id, name, domain, settings, billing_info, created_at
• users: id, org_id, role_id, name, email, phone, password_hash, meta
• roles: id, name, permissions
• permissions: id, name
• appointments: id, org_id, user_id (patient), staff_id (doctor), service_type, start, end, status, created_by, notes
• calendars: id, org_id, owner_id, timezone, visibility
• inventory_items: id, org_id, sku, name, category, qty, unit, price, details, location, reorder_threshold
• inventory_transactions: id, item_id, org_id, change, reason, actor_id, created_at
• chatbot_sessions: id, org_id, user_id, messages (json), resolved_flag, escalation_id
• messages: id, session_id, sender_type, content, metadata, created_at
• campaigns: id, org_id, name, content_template, image_asset_id, audience_filter, schedule
• assets: id, org_id, url, type, metadata
• notifications: id, target, channel, status, payload, sent_at
• audit_logs: id, actor_id, org_id, action, resource, created_at

Key API flows / endpoints

• Auth: POST /auth/login, POST /auth/register, POST /auth/refresh
• Tenant: POST /orgs, GET /orgs/:id (admin)
• Users: CRUD users and roles
• Appointments: GET /availabilities?provider_id&date, POST /appointments, PATCH /appointments/:id (reschedule/cancel)
• Inventory: GET /inventory?query, POST /inventory, PATCH /inventory/:id
• Chatbot: POST /chat/message (proxy to LLM + local hooks), GET /chat/sessions/:id
• Campaigns: POST /campaigns/preview, POST /campaigns/send
• Notifications/webhooks: POST /webhooks/whatsapp-callback

Chatbot integration pattern

• User sends message -> backend receives -> pre-process (intent/entity extraction) -> run inventory/appointment lookup hooks -> construct context -> call LLM API with context -> post-process LLM result (if not confident, escalate to human) -> respond via UI/WhatsApp.
• Keep structured tools: inventory_check(item_name) and appointment_check(provider, date) that LLM can call or that are run by the backend before prompting.

Multi-tenancy & security

• Tenant isolation: row-level security in Postgres or separate schemas per org
• Data encryption at rest and in transit
• Audit logs for PHI access; role-based access control strictly enforced
• Compliance: design for HIPAA if supporting hospitals (BAA, encryption, logging, data minimization)

MVP scope (priority)

1. Auth + tenant + RBAC
2. Appointment booking + calendar UI
3. Basic inventory CRUD + inventory lookup API
4. Chatbot MVP with hooks to inventory + booking (no image gen)
5. Notifications (email/SMS) for booking confirmations

Phase 2 (after MVP)

• Add image/ad generation and WhatsApp sending
• Campaign automation and segmentation
• Advanced analytics and reporting
• SLA/performance scaling and multi-region deployment

Verification

1. Unit tests for business logic (appointments, inventory adjustments)
2. Integration tests for API endpoints and DB transactions
3. E2E tests for booking flow and chatbot interaction
4. Security review and HIPAA checklist if required
5. Load tests for calendar and chatbot concurrency

Decisions & Assumptions

• Multi-tenant design is required; decide between schema-per-tenant or RLS; recommend RLS for many tenants.
• Hospitals require HIPAA — assume we need BAA and strict controls for that tenant type.
• Use managed services where possible to accelerate time-to-market.

Next immediate actions (pick one and I will produce the artifacts)

• A. Choose tech stack (I will scaffold repo + starter files)
• B. Draft detailed DB schema DDL for PostgreSQL
• C. Draft API contract (OpenAPI) for MVP endpoints
• D. Design UX wireframes for booking + admin panels