Three actors before market open.
Apify scheduled actors run before market open, pulling from federal, state, and private-sector breach disclosure feeds. Three actors total. Each one writes raw output to a staging table.
CASE STUDY · 01 OF 03
Daily breach intelligence assembled from public sources, classified and deduplicated by Claude, routed into one Slack digest per partner. Replaced a multi-source morning-scan ritual that cost each attorney two hours per day with fifteen minutes of curated review.
01 ·Context
Each attorney was scanning fifteen tabs every morning to track new data-breach disclosures across federal, state, and private-sector sources. Two hours per day, per attorney. Outputs went into shared spreadsheets the team had to reconcile against.
The cost was attorney time spent on triage that an entry-level paralegal could not do safely. Some sources required judgment about scope, jurisdiction, or partner-relevance, so the work stayed at the partner level. The bottleneck was structural.
The trigger to ship a system was a missed disclosure. A federal-register entry surfaced four days late because the partner who normally watched that source was on a deposition. The team decided that one missed disclosure was the cost of doing the workflow manually, and the next conversation was about replacing the workflow.
02 ·The system
Apify scheduled actors run before market open, pulling from federal, state, and private-sector breach disclosure feeds. Three actors total. Each one writes raw output to a staging table.
Claude classifies each disclosure on industry, scope, freshness, and partner-relevance. Dedup runs against the prior 30 days of disclosures, hashed on a normalized title plus disclosure date. Confidence threshold gates the auto-route path.
Airtable holds the structured record (disclosure title, classified industry, scope tags, source link, partner-relevance score, dedup hash). Slack delivers the digest.
One Slack digest per partner in #breach-feed, delivered before the workday starts. Each disclosure renders as a one-line summary plus a link to the full Airtable record. Partners read the digest, click into the records that need deeper review, leave the rest.
Source-down retry with exponential backoff. Manual override channel for partners to flag a disclosure for deeper review or escalate a misclassification. Audit log entry per disclosure capturing the classification confidence, the dedup hash, and the routing decision.
03 ·The build
Praxis-led build narrative, week by week. Where design judgment moments landed. What the team learned mid-build. Content fill — copy is placeholder, structure stable.
04 ·Result
What changed, how the team operates differently now, what time was redirected, what scaled because the bottleneck moved. Concrete details, specific numbers. Content fill — copy is placeholder, structure stable.
05 ·Stack
Apify·Airtable·Claude·Slack·Cowork