Project Title: ASAPP CRM — AI-Powered Real Estate Lead Management

Short Description: A role-based real estate CRM that centralizes lead capture, assignment, follow-ups, communication, reporting, and AI-powered sales workflows.

Project Description:

I led the full-stack development of ASAPP CRM, a real estate sales platform designed to help teams manage leads, communication, follow-ups, and daily operations from one centralized system.

The Challenge

Real estate teams were receiving leads from multiple channels and relying on disconnected tools for assignment, communication, and follow-ups. This made it difficult to track lead activity, maintain accountability, and respond to opportunities on time.

The Solution

I helped create a scalable CRM platform featuring:

• Role-based dashboards for administrators, managers, and agents • Automatic lead capture from social channels • Round-robin and manual lead assignment • Complete activity history when leads are transferred • SMS, WhatsApp, and email communication from the lead profile • Follow-up calendar for overdue, upcoming, and completed activities • Real-time lead pipeline and conversion monitoring • AI-powered lead scoring and sales forecasting • Next-best-action recommendations • AI chatbot for lead qualification • Context-aware email and SMS drafting • Mobile access and live lead-count widgets

The Result

ASAPP CRM gave sales teams a clearer view of their pipeline, improved lead ownership, and made follow-ups easier to manage. Its automated follow-up workflow also helped reduce the missed-meeting ratio by 2%.

My Role: Lead Full-Stack Developer

Skills: CRM Development, TypeScript, Node.js, Express.js, MongoDB, REST APIs, RBAC, AI Integration, Workflow Automation

AI Voice Project Copilot for Stakeholders 🚀

My Role:

AI Solutions Architect · Voice Agent Developer · RAG Architect

Output:

Built an AI voice interface that allows stakeholders to communicate directly with a project's knowledge and operating context. The agent can retrieve information from a large internal knowledge base, explain features and processes, answer status questions, surface relevant suggestions, and create notes for the project team.

The architecture combines conversational AI, RAG, structured context, APIs, and controlled actions - turning project knowledge into an always-available voice copilot.

Deliverables:

Voice Agent · Project Knowledge RAG · Conversational Retrieval · Action Integration · Stakeholder Copilot