Case study / Data and intelligence
Messy county permit records, classified and monitored automatically
County permit records ingested, classified, and enriched automatically, then pushed out as monitored alerts.
- Client
- Permit Hound, permit intelligence
- Industry / size
- Permit data and construction intelligence
- Systems
- County permit sources, Classification pipeline, Alerts
Context
County permit records are the raw material for permit intelligence, but they are messy: scattered across sources, inconsistently formatted, and built for filing rather than analysis.
The problem
Turning those records into something useful meant manual lookups, one at a time. That does not scale, it misses records, and the useful signal arrives late, if at all.
What we built
We built a pipeline that ingests county permit records, classifies and enriches them automatically, and pushes the relevant ones out as monitored alerts. The messy source data becomes structured, searchable, and watched, without a person doing lookups.
The result
More than 40,000 permits are classified automatically every month, and manual lookups are gone. Instead of searching for permits, the relevant ones arrive as alerts.
Results
Permit lookups
Manual, one at a time Ingested and classified at scale
Impact
The grunt work of permit research runs on its own, and the signal shows up as an alert.
- More than 40,000 permits classified automatically each month
- Messy, inconsistent county records normalized and enriched
- Relevant permits surfaced as monitored alerts instead of manual searches
How we estimate this: Value is the manual lookup time removed plus the coverage gained from classifying every record rather than sampling by hand.
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