Building Qlauson — The Quality Tracking Platform for Any Industry
Hey everyone,
I've been working on Qlauson for a while now and just opened early sign-ups.
What it is:
A quality tracking platform that helps you organize audits, deviations, corrective actions, and claims — all in one place. Built for teams and consultants who need something simpler than a legacy QMS, but more structured than spreadsheets.
Why I'm building it:
Quality teams, consultants, and ops people spend hours digging through spreadsheets to track what went wrong, who's fixing it, and whether the fix actually worked. Most tools are either too complex (heavy enterprise QMS) or too generic (general work trackers that don't understand quality workflows). I wanted something that fits right in the middle — simple, fast, and designed for how quality work actually gets done.
How it works:
You log an order, a campaign, a shipment, an inspection — whatever your industry calls it. If everything goes fine, you close it. If something goes wrong, you flag a deviation, assign it, track the fix (corrective action), and verify it's resolved. Qlauson's Copilot handles the heavy lifting — you just tell it what's happening, and it creates the records, assigns owners, and tracks everything to closure.
At review time, your KPIs are already waiting: what went right, what went wrong, and what still needs attention.
Where it's at:
Early stage. Early sign-ups are open at qlauson.com. Free tier for individuals and small teams. Paid plans coming later for consultancies and larger teams.
What I'm figuring out right now:
Pricing that makes sense for consultants managing multiple clients
How to keep the platform flexible enough for any industry without becoming generic
Building the Copilot to handle natural language input smoothly — so you can just type "open order #1002, item #42 damaged" and it does the rest
What's next:
Onboarding early users, collecting feedback, and iterating fast.
Happy to answer questions or hear from anyone in Quality, Ops, or anyone tracking work that needs to be done right. If you've built something in this space, I'd love to learn from you.
Cheers,
Qlauson team
#buildinginpublic #indiehackers #qualitymanagement #worktracking #startup
Really interesting niche — root cause analysis in quality management is genuinely underserved by AI tooling. The insight that most tools track what happened but not why is spot on. Curious: are you using a structured causal graph approach under the hood, or more of an LLM-based inference from the audit data? Also, for regulated industries (pharma, medical devices), how are you thinking about auditability and explainability of the AI conclusions? That's usually the first question compliance teams ask.
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