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Case study Champdatatek

Seventy automations, and no way to tell which had died

The client provides labour poster compliance, annual filings, and regulatory services to businesses across the USA, powered by 70+ scrapers and automations spread over multiple servers. As the ecosystem grew, nobody could answer the only question that mattered: is everything still running, and is the data any good?

Services Monitoring platform & dashboard engineering
Category Automation observability
Client ChampDataTek
Stack .NET · Windows Services · Next.js · Supabase
ChampDataTek
The problem

The automation ran the business, and nothing watched the automation.

Scrapers fail quietly. A broken job looks exactly like a job with nothing to report, until a compliance deadline proves otherwise.

✓70+ scrapers across multiple servers, tracked manually ✓No central view of which jobs had run or failed ✓Silent failures discovered days later, or by a client ✓Troubleshooting starting from scratch every time ✓No data-quality checks on what was collected ✓Exporting data a manual, repeated chore

What it was costing

✓Compliance services built on data nobody had verified ✓Engineering time spent hunting rather than fixing ✓Scaling the automation ecosystem increasing the risk ✓Client trust exposed to a failure nobody had noticed
Our approach

Build the control room

A single portal where every automation reports its own health, and a failure announces itself instead of waiting to be found.

✓Centralised portal covering all 70+ automations ✓Per-job health monitoring and run history ✓Failure notifications the moment a job breaks ✓Data-quality checks on collected records ✓Streamlined export workflows ✓Quick identification of which job failed, and where
Core capabilities

What it does now

Real-time visibility across the whole automation ecosystem.

✓One dashboard for every scraper and automation ✓Health monitoring with run history per job ✓Automated failure alerting ✓Data-quality validation on ingested records ✓Self-serve data export ✓Troubleshooting measured in minutes, not days

Every month you leave it manual, you pay for it in salary.

Bring us the workflow that costs you most. Thirty minutes with an engineer, and you leave with the map whether you hire us or not.

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