Software Developer

Abuzar Siddiqi

iOS • Web • AI Applications

Building scalable applications with SwiftUI, React, and AI. Founded a VIT-TBI backed startup and shipped production systems end-to-end.

"Building production-grade iOS, web, and AI applications"

Abuzar Siddiqi in blazer Abuzar Siddiqi in hoodie

Summary

Built for Real-World Scale

Software Developer with production experience across iOS, web, and AI applications using SwiftUI, React, Python, and Firebase. Founded and built KwikCut, a VIT-TBI backed startup, shipping both customer-facing and operational products. Strong in system architecture, rapid execution, and team leadership. Currently seeking Software Engineering, AI, and Full Stack roles.

Professional Experience

Founder - KwikCut

Founder & Lead Developer

October 2024 - September 2025

Selected for VIT-TBI Pre-incubation

Built a full salon booking ecosystem with an iOS client and a web operations dashboard. Drove product architecture, shipping, and daily execution.

Key Achievements
  • Built iOS app from scratch: login, booking flow, and push notifications using Swift + Firebase.
  • Created web dashboard for salon owners with real-time appointment and slot management.
  • Architected database, auth, and deployment pipeline across mobile and web surfaces.
  • Led 4 interns through code reviews, mentoring, and development planning.
SwiftUI Firebase React
KwikCut logo and tagline poster
Kwikcut - Get Cut Quick

Case Study: KwikCut Salon Booking Platform

Designed as a two-surface product: a customer iOS app for booking and a web dashboard for salon operations. Built a Firebase-backed real-time workflow for booking events, status updates, and notifications. Reduced operational friction by consolidating schedule management, customer intake, and live appointment visibility.

Featured Projects

AI, iOS, and Web Systems

January 2026

Daily AI Companion [KwikLyze]

Local-first voice assistant focused on productivity automation and natural language system control. Built for near real-time interaction with offline reliability.

  • Achieved ~200ms voice-to-action latency for real-time automation workflows.
  • Implemented offline pipeline using Whisper (STT), Vosk (wake-word), and Qwen 2.5 LLM.
  • Added proactive scheduling and routine-based productivity orchestration.
ElectronPythonReactJavaScriptQwen 2.5WhisperVosk
Wake Word
Vosk
Speech-to-Text
Whisper
Reasoning
Qwen 2.5
Automation Layer
System Tasks

Technical Skills

Engineering Stack

Languages

JavaC++CPythonSwiftJavaScript

Frameworks & Tools

SwiftUIReactElectronFirebaseNode.jsGit

AI & ML

Qwen 2.5WhisperVoskPrompt Engineering

Databases

FirebaseMySQLMongoDB

Core CS

DSAOOPSystem DesignMulti-threading

Contact

Let’s Build Something Useful