Mirza Shahbaz Ali Baig

Businesses in the service industry rely on fragmented tools — separate systems for scheduling, payments, client management, and marketing — with no unified platform built for their workflow. Existing solutions are either too generic or too expensive to white-label at scale.

Architecting a full multi-tenant B2B SaaS platform from the ground up. Each tenant is fully isolated at the data layer via a tenant-scoped Prisma middleware. Built a plugin-based PayableHandler registry with a central PaymentOrchestrator owning all Stripe Connect logic — handling packages, gift cards, memberships, and wallet credits under a single payments interface. A trigger-filter-action Automation engine (similar to Zapier Flows) was designed for internal approval, with BullMQ workers processing async jobs. Cloudflare R2 handles multi-tenant media with signed URL uploads. Resend powers transactional email with per-tenant custom domain verification.

Core modules — scheduling, payments, client CRM, and automation — actively in development. Architecture reviewed and approved for production scale. Targeting feature parity with leading vertical SaaS competitors.

An educational board serving 15,000–20,000 students needed real-time WhatsApp communication — results, alerts, announcements — with zero message loss and a live agent dashboard.

Designed a 4-phase webhook → queue → WebSocket architecture on Meta Business API directly (skipping Twilio to eliminate per-message costs at scale). Inbound webhooks validate HMAC-SHA256 signatures and enqueue instantly to BullMQ — returning HTTP 200 before any processing to prevent Meta retry storms. Workers handle idempotency, persistence, and Redis Pub/Sub. A Socket.IO gateway routes live events to agents by room.

Message visibility latency: 5,000ms → under 1,000ms. Polling load reduced by 92%. Live in production serving 15,000+ students.

Most AI chatbot tutorials produce demos that break in production — no tool-calling reliability, no memory, no structure.

Built an industry-ready agentic chatbot from scratch with LangGraph state machines, persistent memory, real-world API tool-calling, and a production-grade folder structure designed for extension.

A reusable agentic foundation — not a demo. Can be dropped into any client project requiring conversational AI with external API access.

Needed a complete real-world backend to master MERN — not a CRUD tutorial but a platform with actual complexity: auth, media, social graph.

Built a full YouTube-inspired platform — video uploads to Cloudinary, channel management, subscriptions, likes, comments, watch history, and JWT-based auth with refresh token rotation.

A complete production-pattern MERN backend serving as a reference architecture for future client projects.