Atlas DeskIn Development
An AI-first customer support and developer ticketing platform engineered to autonomously resolve, summarize, and route issues.
The Challenge
For engineering and support teams, the biggest operational drag isn't fixing bugs—it's the endless hours wasted triaging duplicate tickets, deciphering vague bug reports, and hunting for context. Traditional helpdesks are just dumb databases; they wait for humans to do the heavy lifting. We needed a system that actively reduced the noise.
The Solution
I architected an intelligent, multi-agent ticketing layer that sits in front of the human team. Custom AI agents autonomously ingest, categorize, summarize, and route incoming issues, effectively acting as an automated L1 support tier before a human ever opens the dashboard.
The Story
I built Atlas Desk out of sheer personal frustration. I didn't want another place to just *store* tickets; I wanted a platform that actively *worked* them. The hardest engineering problem was building trust into the system. Designing LLM-powered agents to read completely unstructured data and accurately assign priority levels—without ever hallucinating a critical P0 alert or ignoring a real one—required rigorous prompt engineering, confidence-scoring, and fallback safety mechanisms.
What I Learned
Building a multitenant SaaS from scratch taught me how to balance complex backend AI orchestration with a lightning-fast frontend. I realized that a brilliant AI model is completely useless if it's wrapped in a clunky UI, which pushed me to deeply master Next.js App Router to deliver a responsive, enterprise-grade user experience.