MCPProbe: Building a Diagnostic Layer for the Model Context Protocol
When the Model Context Protocol became the de facto standard for AI-to-tool communication in 2025, the ecosystem around it grew fast. Servers proliferated. Clie...
Replacing manual workflows with autonomous AI systems to cut operational costs, eliminate bottlenecks, and drive measurable ROI for scaling businesses.

85% Manual Workload Reduction
Built an autonomous digital workforce platform that fully automates customer support and operational tasks across WhatsApp, Discord, and Gmail. Designed to replace repetitive human workflows and drastically cut operational overhead.
Offline AI Agent. Any Machine. Zero Install.
Engineered a portable AI coding agent that runs entirely off a USB drive — no install, no residue on the host. Packages Ollama + opencode for all 5 platforms (Windows, macOS Apple Silicon/Intel, Linux x64/ARM64) from a single stick. Built for airgapped environments: banks, hospitals, defense contractors, and privacy-sensitive codebases where cloud AI is blocked.
Instant Codebase Discovery
Engineered an AI-powered search engine for massive codebases, currently used by 200+ engineers. Drastically reduces onboarding time for new developers and eliminates hours wasted searching for undocumented architecture.
High-Performance Embedded Database
Architected a custom embedded database in Rust that prioritizes speed and security. Reached 2,400+ downloads by providing enterprise-grade AES-256 encryption and zero-latency data retrieval for performance-critical applications.
I am a Full-Stack AI Engineer building systems that don't just respond — they execute, optimize, and scale. Based in Lahore, I build autonomous AI operations that eliminate manual bottlenecks and scale without increasing headcount.
With a background in RAG pipelines and agentic orchestration, I deliver production systems that turn unstructured data into automated business outcomes.

Architecting AI agents that automate complex routing and decision-making, slashing operational overhead.
Building end-to-end AI products that integrate LLMs directly into business logic to drive immediate, measurable results.
Deploying resilient, production-ready systems that handle high-volume workflows while maintaining data integrity and performance.
Architecting the backbone for enterprise AI, focusing on decision-making latency and large-scale data ingestion.
Developing robust backend architectures designed for zero-downtime and high-throughput mission-critical tasks.
Engineering seamless, high-conversion interfaces that prioritize speed, accessibility, and measurable user engagement.
Optimizing the storage, retrieval, and integrity of complex datasets for both structured and unstructured environments.
Streamlining delivery through CI/CD automation, container orchestration, and multi-tenant security protocols.
DeveloperHub
Pioneered the integration of agentic workflows and RAG systems. Focused on optimizing LLM response latency and architecting multi-step autonomous chains.
Virtual University of Pakistan
Presidential Initiative for AI & Computing
End-to-end design and deployment of an agentic system that handles a specific high-volume operational task — fully autonomous, production-ready, integrated into your existing stack.
A working autonomous system replacing a job function, not a demo.
All engagements start with a free strategy call.
When the Model Context Protocol became the de facto standard for AI-to-tool communication in 2025, the ecosystem around it grew fast. Servers proliferated. Clie...
The first time someone asked me "can I use your AI coding setup on a locked-down work laptop with no admin rights?", I said no. A month later, I shipped CodeSti...
There is a persistent myth about AI coding agents that needs to be addressed directly: the idea that they fail because they are not smart enough. The narrative ...