Case study · SaaS

AslasChatAI-powered chatbot SaaS — automated customer interactions and NLP-based lead capture.

SaaS Platform · Final Year Project (FAST) · 2026

SaaS

Multi-tenant chatbots

NLP

Auto lead extraction

Real-time

Chat + analytics

AslasChat preview

The challenge

Small businesses wanted to deploy AI chatbots on their websites without engineering teams — and they needed those bots to actually capture qualified leads, not just answer FAQs. Existing tools were either too generic, too expensive, or required code.

What I built

Built a multi-tenant SaaS platform on NestJS + Next.js: scalable REST APIs, Firebase authentication, secure token handling, and role-based access. Integrated Google Gemini for NLP-based extraction of names, emails, and phone numbers directly from natural chat flow. Real-time chat surfaces, dashboards, and analytics built with MongoDB and Tailwind.

  • Multi-tenant SaaS architecture with isolated workspaces
  • Firebase auth + RBAC + secure token handling
  • Gemini-powered NLP extraction for names / emails / phones
  • Real-time chat, conversation dashboards, and analytics

Outcome

Tenants spin up bots in minutes, see conversations in real time, and watch qualified leads land in their dashboard automatically. The platform is the foundation of my Final Year Project at FAST University.

Working on something similar? I’d love to hear about it.

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