Noman Jalal's Work | ContraWork by Noman Jalal
Noman Jalal
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Noman Jalal

Experienced full stack engineer with 10+ years of experience

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Cover image for AI Powered Planning & Knowledge
AI Powered Planning & Knowledge Workflow Platform PlanSpace is a modern AI powered platform focused on intelligent planning, contextual information handling and workflow organization. The system was designed to combine structured data workflows with AI assisted contextual processing to improve operational visibility and decision making. I worked on backend architecture, AI workflow integration, retrieval systems, API orchestration and scalable infrastructure design. The platform leveraged modern AI patterns for contextual reasoning, semantic retrieval and intelligent workflow execution while maintaining production reliability and scalable system architecture. The implementation included AI assisted processing pipelines, backend orchestration layers, vector based contextual retrieval, automation workflows and extensible infrastructure capable of supporting future AI native operational features. The focus was not only on rapid product delivery but also on long-term maintainability, modular architecture and scalable deployment practices.
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Cover image for AI Powered SaaS Platform for
AI Powered SaaS Platform for Intelligent Business Workflow Execution HiByron is an AI powered SaaS platform focused on streamlining business workflows through intelligent automation, conversational AI and AI assisted operational infrastructure. The platform was designed using an AI first engineering workflow with tools like Claude Code, Cursor, and modern LLM infrastructure to accelerate development while maintaining production grade architecture and scalability. I worked on architecting scalable backend systems, AI workflow orchestration, API integrations, and intelligent automation pipelines that allowed the platform to execute complex business operations efficiently. The system combined modern AI tooling with production focused engineering practices to support rapid iteration, maintainability and reliable deployment. The architecture included AI driven workflow execution, backend orchestration layers, automation systems, contextual processing pipelines and scalable infrastructure designed for long term product evolution rather than short term MVP limitations.
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Cover image for Production AI Voice Agent Infrastructure
Production AI Voice Agent Infrastructure for Lead Qualification & Appointment Automation Project Overview: NextGenCalls is an AI powered voice automation platform designed to handle real business conversations through autonomous AI voice agents. The system was built to automate lead qualification, appointment booking, customer interaction workflows and conversational support operations while maintaining natural real time communication. Unlike traditional IVR systems or scripted bots, the platform uses conversational AI, contextual memory and workflow orchestration to manage dynamic interactions across inbound and outbound calls. The infrastructure was designed for scalability, low latency voice streaming and reliable production deployment. The Problem: Businesses handling high volumes of customer calls often struggle with missed leads due to delayed responses expensive support operations repetitive qualification workflows inefficient appointment scheduling inconsistent customer interactions Traditional IVR systems create poor user experiences because they rely on rigid menu trees and cannot adapt dynamically during conversations. The goal was to build an AI voice system capable of handling conversations naturally while executing operational workflows autonomously. Technologies Used: OpenAI GPT-4o Claude Vapi Twilio ElevenLabs Whisper Deepgram FastAPI Python Node.js PostgreSQL Redis n8n Webhooks & APIs Docker AWS
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Cover image for Multi Agent AI Workflow System
Multi Agent AI Workflow System for Autonomous Business Operations Project Overview: Blitzday AI is an AI driven workflow automation platform designed to execute complex business operations through autonomous multi agent systems. The platform combines LLM reasoning, workflow orchestration, automation pipelines and contextual decisio -making to reduce manual operational work and improve execution efficiency. Instead of relying on static automations, the system was designed to coordinate intelligent agents capable of planning, retrieving context, using tools and executing multi step workflows dynamically. Technologies Used: OpenAI GPT-4o Claude LangChain LangGraph CrewAI Python FastAPI Node.js PostgreSQL Redis n8n Supabase Docker AWS APIs & Webhooks
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