--- title: "Troubleshot Case Study: From Audit to Live Platform | George Rios" description: "How George Rios took Troubleshot from a one-week audit of a lab prototype to a live platform that captures plant-floor radio calls for maintenance teams, then handed it over to the founder in four months." url: https://georgerios.com/case-studies/troubleshot author: George Rios --- Case study · Manufacturing # Troubleshot: from a one-week audit to a live, founder-owned platform in four months When a machine goes down, the operator radios maintenance. That call holds the most useful context about the failure, and nobody writes it down. Troubleshot captures it automatically. Its founder had proven the idea on a lab setup. I started with a one-week audit, rebuilt it into a live platform, moved the radio capture to the cloud, and handed the whole thing over to his own account. [Book a free 30-minute call ](https://cal.com/georgerios/30min) [All case studies ](https://georgerios.com/case-studies) **1 week** Audit to a clear plan **2 days** Rebuild to live **20 findings** From testing, all shipped **\~4 months** Prototype to hand-over At a glance ## A proven idea, turned into a product the founder owns What started as a fixed-scope, one-week audit grew into a full rebuild, a hardware integration, and a hand-over to the founder’s own infrastructure. Every phase after the audit was driven by his own testing. | Client | Troubleshot LLC; founder Zach Kauffman | | ------------ | ------------------------------------------------------------------------------------------------------------------------------ | | What it does | Captures plant-floor radio calls and turns them into context for the next technician | | My role | Technical lead and sole engineer: audit, architecture, build, deployment, and ongoing support | | Timeline | Late May 2026 (audit) to September 2026 (hand-over); support ongoing | | Shipped | The web app (installs on phones), a docs site, a marketing site, and the upload software for TRN-1, the radio-recording device | | Built on | Cloudflare, with OpenAI for transcription and summaries, and a Raspberry Pi radio receiver | | Quality | 114 automated tests, and releases that check themselves before and after going live | The starting point ## A convincing demo, on one network On May 22, 2026, the founder’s lab setup ran the full loop for the first time: radio call in, useful context out. It was held together by three separate pieces, all on one local network. 01 · The app ### Lived in one browser Every symptom, fault, and fix was saved in the browser itself. Nothing synced between people or devices. 02 · Transcription ### Ran on a laptop A small service on a laptop received the radio clips and sent them to OpenAI to be transcribed. 03 · TRN-1 ### A radio recorder A Raspberry Pi with a radio receiver recorded the plant’s radio traffic and uploaded clips over the local network. It couldn’t support a pilot customer. Zach hired me for a fixed-scope, one-week audit with three questions: what’s demo-ready, what will break in front of a customer, and what’s the fastest path to pilots without rebuilding for its own sake? How it evolved ## Keep what works. Rebuild everything around it. The audit’s verdict was to keep the capture loop Zach had proven and rebuild everything around it on a real backend. The rebuild went live within two days. Every phase after that answered a specific need: a demo, a round of testing notes, an error in the device logs, or Zach taking full ownership. Late May **Audit sprint.** A one-week review of the prototype, its data, the AI workflow, and the demo setup, ending in a recommendation: keep the capture loop, rebuild on a real backend. Jun 17–18 **Platform rebuild, live on day one.** A proper backend and database, a new web app, company sign-up, docs and marketing sites, and an in-app AI assistant. Jul 6 **Radio capture moves to the cloud.** The laptop service was retired; transcription now runs inside the platform, and TRN-1 uploads to it directly. Jul 7–8 **Demo-readiness fixes.** Log and escalate in one step, a findings workflow for responders, photos from the phone camera, and an Engineering tier on the escalation ladder. Jul 14–16 **Round two.** All 14 findings from Zach’s testing shipped the next day. The app now installs on phones, and a review closed a permissions gap. Sep 14 **Device hardening.** Traced the radio device’s occasional errors to their root cause and fixed it there. Sep 28 **Hand-over.** Domain, database, files, and services moved to Zach’s own Cloudflare account, with a plain-language owner’s guide. How I built it ## So a small team can change it without fear 01 · One rulebook ### Rules live in one place The escalation ladder, shift handoffs, solution review, and who can see what are defined once. The server, the app, and the tests all use the same rules, so they can’t drift apart. 02 · No servers ### Nothing to patch Everything runs on Cloudflare. There are no servers to maintain, costs stay low at pilot scale, and the whole platform runs on a laptop for development. 03 · Many companies ### Separate from day one Each company gets its own workspace, tied to its email domain. Every record and file is kept separate by company, and audio and transcripts are visible to admins only. 04 · Root causes ### Fix the cause, not the symptom The radio device logged about 8 errors a week out of roughly 115,000 check-ins. I traced them to brief database hiccups on a step the device never needed, removed that step, and added targeted retries. 05 · Releases ### Releases can’t skip steps One command runs the tests, backs up the data, deploys, and checks the live site, and prints how to roll back if anything fails. 06 · Reviews ### Regular review sweeps Structured reviews looked for permission gaps and fragile code. One closed a gap on approved solutions, and the automated test suite grew to 114 tests. Live · ready for pilots Troubleshot / 2026 ## A product Zach owns end to end, and can demo to customers What used to need three programs on one local network is now one hosted platform. An operator logs a fault, presses Escalate, and makes their usual radio call. When the technician opens the issue, a context card built from the call’s transcript is already waiting. No extra work from the operator. [Talk about your prototype ](https://cal.com/georgerios/30min) It started with a short, fixed-scope audit, the same first step as my [AI-built app audit](https://georgerios.com/ai-app-audit). What Zach has now 4 01 **Context captured automatically** The radio call becomes a transcript-backed card for the next technician 02 **A complete maintenance workflow** Symptoms and faults, an Operator → Maintenance → Controls → Engineering escalation ladder, shift handoffs, and a reviewed library of step-by-step fixes with photos 03 **Live everywhere it needs to be** The web app on phones and desktops, a public docs site, and a marketing site with working contact and demo forms 04 **Full ownership** Everything runs in his own account. Every record and all 37 stored files were checked against the originals, and a plain-language owner’s guide sits alongside the code ### The result, judged - One-week audit turned into a clear plan to reach pilots Pass - Rebuilt platform live within two days Pass - 20 findings from two rounds of testing, each shipped within a day or two Pass - Handed over to the founder’s own account, every record verified Pass - Pilot customers Up next Your prototype ## Have a demo that works, but not in front of a customer? A one-week audit tells you what’s demo-ready, what will break in front of a customer, and the fastest path to pilots. [Book a free 30-minute call ](https://cal.com/georgerios/30min) [AI-built app audit ](https://georgerios.com/ai-app-audit) --- Contact: george@georgerios.com · Book a call: https://cal.com/georgerios/30min · Services summary for agents: https://georgerios.com/llms.txt