Project Info
Inspiration
During my summer internship, I watched senior engineers earning $150-200/hour spend hours daily answering the same Jira support tickets repeatedly. "How do I access the production database?" "Where's the CSV export button?" These weren't complex problems—they were fixable UX issues nobody had time to address because they were too busy firefighting. I calculated the cost: our 50-person team wasted $180,000 annually on repeat questions. When I looked at customer support teams handling thousands of tickets monthly, the problem was exponentially worse. SupportGPS was born from one insight: what if AI could automatically detect these patterns, aggregate the solutions already hidden in resolved tickets, and distribute that knowledge everywhere—Slack for dev teams, GitHub for documentation, Reddit for customers? Instead of answering the same question 62 times, fix it once and eliminate 73% of future tickets.
What it does
SupportGPS transforms support chaos into automated productivity gains through AI-powered pattern detection and multi-platform knowledge distribution. Core Features: Intelligent Pattern Detection: Analyzes support tickets (via Zendesk MCP integration or CSV upload) to identify recurring issues. Calculates exact cost impact: 62 tickets about CSV export button = $1,550/week waste = $80,600 annually. Intelligent Pattern Detection: Analyzes support tickets (via Zendesk MCP integration or CSV upload) to identify recurring issues. Calculates exact cost impact: 62 tickets about CSV export button = $1,550/week waste = $80,600 annually. Automated Dev Team Notifications (Slack): Instantly alerts developers when critical patterns surface with full context: problem description, aggregated solutions from 62 support conversations, temporary workarounds, and ROI justification ($80K/year savings). Engineers triage via emoji reactions—no meetings needed. Automated Dev Team Notifications (Slack): Instantly alerts developers when critical patterns surface with full context: problem description, aggregated solutions from 62 support conversations, temporary workarounds, and ROI justification ($80K/year savings). Engineers triage via emoji reactions—no meetings needed. Self-Documenting GitHub Integration: Auto-creates GitHub discussions with technical specs and temporary fixes. Updates wiki documentation automatically. Developers get complete context without leaving their workflow. Self-Documenting GitHub Integration: Auto-creates GitHub discussions with technical specs and temporary fixes. Updates wiki documentation automatically. Developers get complete context without leaving their workflow. Customer Self-Service (Reddit): The breakthrough feature—aggregates all support agent solutions and auto-generates Reddit explainer posts. When users Google "how to export CSV [product]," they find instant answers instead of opening tickets. Proven 73% ticket reduction after publication. Customer Self-Service (Reddit): The breakthrough feature—aggregates all support agent solutions and auto-generates Reddit explainer posts. When users Google "how to export CSV [product]," they find instant answers instead of opening tickets. Proven 73% ticket reduction after publication. Visual Asset Generation (Nano Banana MCP): AI-generated annotated screenshots and step-by-step visual guides embedded in Reddit posts and documentation. Visual Asset Generation (Nano Banana MCP): AI-generated annotated screenshots and step-by-step visual guides embedded in Reddit posts and documentation. Real-Time Dashboard: Upload CSV or connect Zendesk for instant visualization of which issues waste the most time/money. Prioritizes fixes by ROI impact.
Challenges we ran into
Biggest technical challenge: synthesizing 62 different support agent responses into one accurate Reddit post without the AI inventing fake solutions. Problem: Simple summarization loses specifics, extractive methods keep contradictions. Solution: Implemented majority-vote logic (if 50/62 agents say "bottom-left," that's canonical), preserved exact quotes from highest-rated responses, added human review gate before publication. Result: Zero false information in published content. Real-Time Dashboard: Upload CSV or connect Zendesk for instant visualization of which issues waste the most time/money. Prioritizes fixes by ROI impact. Challenges we ran into Biggest technical challenge: synthesizing 62 different support agent responses into one accurate Reddit post without the AI inventing fake solutions. Problem: Simple summarization loses specifics, extractive methods keep contradictions. Solution: Implemented majority-vote logic (if 50/62 agents say "bottom-left," that's canonical), preserved exact quotes from highest-rated responses, added human review gate before publication. Result: Zero false information in published content.
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Technology
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