MageTech ServiceFlow

MageTech ServiceFlow

Never Miss a Service. Never Miss a Follow-up.

Section 01 · Commercial Proposition

Customers don't care about the technology stack. They care about one thing: "Will this help me get more repeat service jobs and stop losing customers because we forgot to follow up?"

This is the cycle that matters for an AC, RO, appliance, pest-control, solar or maintenance company. Every service job the platform records automatically schedules the next service reminder and a post-service follow-up — building a self-replenishing pipeline of repeat revenue.

Section 02 · Stack

A modern, containerised stack: Java 21 + Spring Boot on the backend, Next.js 16 on the frontend, PostgreSQL with row-level security for hard tenant isolation, Redis for performance and RabbitMQ for asynchronous notifications and reminders.

Section 03 · Architecture

Deployment overview (Phase 1): Vercel/nginx (Next.js 16) → HTTPS /api/* → AWS EC2 (Nginx/ALB, Spring Boot) → PostgreSQL 16, Redis 7, RabbitMQ 3.13.

Request
  –> Nginx/ALB –> /api –> Spring Security (JWT) –> TenantFilter | set TenantContext
        v
  Controller –> Service –> Repository –> TenantAwareDataSource
                                          | SET app.current_tenant=<id>
                                          v
                          PostgreSQL 16 with FORCE ROW LEVEL SECURITY

Every tenant-scoped query is filtered twice: the application layers its tenant_id predicates on index-aligned (tenant_id, …) indexes, and PostgreSQL row-level security enforces the same boundary at the database — so a buggy query can never leak cross-tenant data.

Asynchronous notifications (RabbitMQ): Publisher (job status change, follow-up, subscription event) → publish JSON NotificationMessage → serviceflow.notification.exchange (direct, durable) → routing key serviceflow.notification.send → serviceflow.notification.queue → @RabbitListener consumer → persist IN_APP notification and fan out to EMAIL / SMS / WhatsApp providers. JSON via Jackson2JsonMessageConverter; poison-message dead-lettering planned for Phase 2. Redis supports rate limiting, the JWT denylist and hot dashboard reads.

Reminder engine: per-tenant fixed-delay scheduler (Spring @Scheduled) scans equipment.next_service_date − rule.days_before <= today; reminder_rules (service_category, days_before INT[], channels); dedupe via reminder_logs unique (tenant, equipment, rule, channel, days_before); insert reminder_log (PENDING) → publish to RabbitMQ → deliver channel (IN_APP · EMAIL · SMS) → mark SENT / FAILED (+ error_message).

Module boundaries (bounded contexts): com.magetech.serviceflow — config (Security, Web MVC, Redis, RabbitMQ, OpenAPI, JPA auditing, Jackson) · shared (ApiResponse/PageResponse, BaseEntity, exception handling) · tenant (TenantContext ThreadLocal, filter, interceptor, data source decorator) · auth (login/register/refresh/logout, JWT provider & filter) · user (users, Role enum OWNER/MANAGER/TECHNICIAN). Domain modules: customer, equipment, technician, job, followup, reminder, notification, subscription.

Security model: short-lived accessToken (15 min, JWT HS256) + long-lived refreshToken (7 days) stored hashed (SHA-256) in refresh_tokens with rotation & revocation; bcrypt passwords; single-use 2-hour password-reset token; RBAC (OWNER everything + billing/settings, MANAGER operations, TECHNICIAN assigned jobs); anti-enumeration on forgot-password; Redis rate limiting auth:login:<email>:<ip> (5/15min) and auth:forgot:<email> (3/hour) with in-memory fallback; Bearer-only auth (no cookies) so CSRF disabled; CORS permissive in dev, restricted in prod; RFC-7807-style 401s via RestAuthenticationEntryPoint.

Scalability roadmap: extract auth-service / notification-service / ai-service when load justifies (monolith-by-module keeps costs low now) · Kafka replaces RabbitMQ for higher-volume eventing (exchange abstraction keeps producers unchanged) · Kubernetes with Helm + HPA once the single EC2 host saturates (RLS stays the isolation invariant) · S3 for customer documents & job photos via pre-signed URLs · read-only replicas for reporting with tenant-aware routing intact.

Section 04 · Multi-tenancy & Data Isolation

Model: shared schema + tenant_id column. Every tenant-scoped table carries a tenant_id UUID and a composite (tenant_id, …) index. One PostgreSQL cluster serves all tenants — the most cost-efficient model for Phase 1 — while isolation is enforced at two independent layers:

-- applied to every tenant-scoped table (V14)
ALTER TABLE service_jobs ENABLE ROW LEVEL SECURITY;
ALTER TABLE service_jobs FORCE ROW LEVEL SECURITY;

CREATE POLICY tenant_isolation ON service_jobs
  FOR ALL
  USING (tenant_id::text = current_setting('app.current_tenant', true))
  WITH CHECK (tenant_id::text = current_setting('app.current_tenant', true));

RLS protected: customers, equipment, technicians, service jobs, follow-ups, reminder rules/logs, notifications, organizations, subscriptions. Not protected (no tenant context): tenants (registry), refresh_tokens (auth). This design scales — moving to Kubernetes or Kafka later does not touch tenancy; RLS stays the isolation invariant.

Section 05 · Feature Catalogue

Section 06 · Commercial — India Pricing (V1)

Positioning: "Never Miss a Service. Never Miss a Follow-up." The Professional plan is the featured offer. Before finalising any price, per-tenant infrastructure + WhatsApp/SMS + email + AI + support cost should be calculated to confirm gross margin.

Starter (₹999): 1 workspace, up to 3 users, customer management, equipment/asset management, service jobs, basic technician management, follow-ups, service reminders, dashboard & basic reports. Professional (₹2,499 ★): everything in Starter + up to 10 users, advanced scheduling/calendar, recurring services, automated reminders, WhatsApp/email integrations, technician mobile interface, invoices & payments, advanced reports, more automation. Business (₹4,999): everything in Professional + up to 25 users, multiple branches, advanced roles & permissions, advanced analytics, workflow automation, API access & webhooks, priority support, AI features with usage limits. Enterprise (₹9,999+/month): multi-branch, custom user limits & workflows, dedicated onboarding, custom reports, SLA, optional dedicated infrastructure, custom AI/automation. One-time implementation / onboarding fee always applies. No base subscription includes unlimited usage.

Section 07 · Billing — Annual Plans

Roughly 10–20% below monthly. Early-adopter annual plan rather than permanently discounting the product.

Section 08 · Implementation Fees & Add-ons

Implementation is never free for business customers. Fees cover business configuration, user setup, service categories, reminder configuration, data import, initial training, channel configuration and basic customisation.

Add-ons (usage-based — never unlimited in base plans)

Section 09 · ServiceFlow Custom

A dedicated "Custom Software" line protects SaaS pricing while capturing deals where companies want ServiceFlow personalised for their exact workflow.

Section 10 · International Pricing

Not a currency conversion of ₹2,499 — a separate international price structure adjusted by market and customer size protects margin where willingness-to-pay is higher.

Why teams choose ServiceFlow