In-house product · Built in-house · 2026

Data intelligence, from signal to dashboard.

An in-house data product that extracts, cleans, enriches, scores and displays market signals in a usable dashboard. We build the kind of systems we would run ourselves.

ClientPlugWheel
IndustryData Systems
Year2026
Data intelligence · WTB Radar

The challenge

The workflow problem we were asked to solve.

The useful signal existed, but it was fragmented across sources, formats and time. Manual tracking could not keep it fresh, and raw extraction alone would only create another messy database. The system needed automation, enrichment, scoring and a dashboard people could actually use.

  • Useful market signals were scattered across many sources.
  • Manual collection was slow and stale by the time it was reviewed.
  • Raw data needed cleaning, dedupe, enrichment and prioritization.
  • Users needed a dashboard, not a dump of unstructured records.

What we built

The build, step by step.

No-code where it fit, custom code where it mattered, and a usable system at the end.

01

Automate the collection path

Scheduled pipelines collect the source data, normalize it and watch for changes over time.

02

Clean and enrich the records

Records are deduped, merged, tagged and enriched so the dashboard reflects usable entities instead of noisy rows.

03

Score the signal

Priority logic turns raw activity into ranked signals, helping users focus on what matters first.

04

Deliver a live dashboard

The final product is a monitored dashboard and workflow surface, not a one-off report.

The results

WTB Radar proves the full data path: automated collection, structured cleanup, scoring and a dashboard experience. It is the same pattern we use for client reporting, market intelligence and operations dashboards.

Dataextracted and cleaned
Scoresfor prioritization
Livedashboard views
Ownedproduct stack

“We prefer to sell patterns we have had to run ourselves.”

PlugWheelOn building internal products

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