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Voice AI / Applied AI engineering

SareeBot AI

A real-time phone-sales pipeline that connects wholesale saree conversations with the tools needed to move an order forward.

Domain
Wholesale saree sales
Focus
Voice and tool orchestration
Core stack
Azure OpenAI GPT-Realtime, FastAPI, FreeSWITCH
Voice connected to commercePhone conversation → inventory, orders and payment links.Conceptual workflow illustration, not a live product screenshot.

The problem

A wholesale sales call involves more than answering questions. A conversation can require customer verification, inventory lookup, product sharing, order creation and payment follow-up. The engineering task was to connect those steps to a voice interface while retaining a path to a human.

My contribution

I built the real-time phone-sales pipeline and its business integrations, including function calling for inventory, orders and customer verification, WhatsApp product sharing, Razorpay payment links, tracking, and human escalation.

The surrounding application included a dashboard, analytics, CRM and inventory workflows.

Engineering choices

The stack combines Azure OpenAI GPT-Realtime, FastAPI, FreeSWITCH, WebRTC, voice activity detection, Whisper and SQLite. The speech layer supports the conversation; function-calling tools connect the agent to inventory, orders, and customer data.

  • Function calling provides an explicit interface for inventory, customer and order operations.
  • WhatsApp supports visual product sharing alongside a phone conversation.
  • Razorpay links provide a separate payment step rather than collecting payment details in speech.
  • Human escalation is part of the workflow when a conversation needs staff involvement.

Proposed next step

Review scenarios involving interrupted calls, unavailable inventory and escalation, with explicit checks before order-changing actions.