Subhajit Mandal

– Architected and deployed an end to end Voice AI Agent integrating Vapi with Dentally CRM using FastAPI, Webhooks, and MCP (Model Context Protocol), enabling fully automated 24/7 appointment booking with zero manual intervention. – Designed 8+ REST API endpoints enabling real-time backend workflows: appointment search, slot booking, patient data updates, and dentist schedule validation all triggered autonomously by the Vapi voice agent. – Implemented production-grade security with HMAC webhook verification, raw body logging, and asynchronous request processing, ensuring reliable and secure communication between voice AI and backend services. – Built a conversation to action mapping engine that translates natural language voice interactions into structured API calls, reducing booking errors and eliminating 100% of manual scheduling overhead. – Deployed containerized FastAPI application to AWS EC2 with Nginx reverse proxy + Uvicorn workers, HTTPS, static IP exposure, and automated environment handling achieving 99.9% uptime. – Designed agent based workflows integrating LLM reasoning with backend APIs to automate real world business operations across the entire patient lifecycle. – Integrated OpenAI Whisper for real time speech to text transcription in voice agent pipelines, enabling accurate natural language understanding across diverse accents and noisy environments. – Leveraged OpenClaw to automate entire business processes including marketing, lead generation, content creation, and multi platform social posting (LinkedIn, Instagram), dramatically reducing manual effort across client campaigns. – Connected OpenClaw with email systems to send personalized outreach emails to leads based on their business profile, increasing engagement rates and streamlining the sales funnel. – Applied OpenClaw across diverse e commerce use cases automating product listing, inventory updates, customer communication, and order lifecycle management to run end to end e-commerce operations with minimal human intervention.

– Developed and deployed Python-based backend services and REST APIs using Flask to support intelligent automation, data processing, and AI ready workflows in the BFSI domain. – Built and maintained RESTful APIs handling secure authentication, backend data exchange, and seamless integration with analytical dashboards, serving 1,000+ daily internal requests. – Designed optimised SQL queries and data models for relational and semi-structured data, supporting feature generation, data validation, and dynamic API responses with 40% faster query execution. – Created data-driven processing pipelines using Python enabling efficient data transformation, enrichment, and preparation for downstream ML and AI-based analytics systems. – Integrated backend services with enterprise tools (JIRA, Git, Confluence), improving traceability, version control, and delivery workflow efficiency. Built AI-ready data pipelines for BFSI datasets, including financial data preprocessing, validation, and analytics aligned with banking compliance requirements.

– Performed data analysis on customer complaints and product performance data to identify root causes, trends, and recurring patterns, informing product quality improvements. – Delivered actionable insights to stakeholders through data driven reports, contributing to measurable reductions in complaint resolution time.