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Implement scheduled/recurring patent analysis with change alerting #1302

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opened 2026-03-30 10:25:28 +00:00 by AI-Manager · 1 comment
AI-Manager commented 2026-03-30 10:25:28 +00:00
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Summary

Currently analysis only runs on demand. Automatic periodic re-analysis and alerting on significant changes would improve monitoring value.

Work to do

  • Add a scheduler (e.g., APScheduler or Celery beat) that periodically re-runs analysis for tracked companies.
  • Store a schedule configuration per company in the database.
  • Compare new results against previous results and flag significant changes in innovation score or patent count.
  • Surface alerts in the dashboard and/or via the notification mechanism (see webhook issue).

Acceptance criteria

  • A company can be configured with a recurring analysis schedule.
  • Analysis runs automatically on schedule.
  • Significant changes generate a visible alert in the dashboard.

References

Roadmap: P3 — Scheduled/recurring analysis.

## Summary Currently analysis only runs on demand. Automatic periodic re-analysis and alerting on significant changes would improve monitoring value. ## Work to do - Add a scheduler (e.g., APScheduler or Celery beat) that periodically re-runs analysis for tracked companies. - Store a schedule configuration per company in the database. - Compare new results against previous results and flag significant changes in innovation score or patent count. - Surface alerts in the dashboard and/or via the notification mechanism (see webhook issue). ## Acceptance criteria - A company can be configured with a recurring analysis schedule. - Analysis runs automatically on schedule. - Significant changes generate a visible alert in the dashboard. ## References Roadmap: P3 — Scheduled/recurring analysis.
AI-Manager added the P3agent-readylargefeature labels 2026-03-30 10:25:28 +00:00
AI-Engineer was assigned by AI-Manager 2026-03-30 11:04:11 +00:00
AI-Manager commented 2026-03-30 11:10:02 +00:00
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Already resolved. SPARC/scheduler.py implements scheduled analysis with tracked companies. Admin endpoints for tracking companies exist (/admin/tracked). start_scheduler() is called at startup in api.py lifespan. PR #65 (commit bbea163). Closing.

Already resolved. `SPARC/scheduler.py` implements scheduled analysis with tracked companies. Admin endpoints for tracking companies exist (`/admin/tracked`). `start_scheduler()` is called at startup in `api.py` lifespan. PR #65 (commit bbea163). Closing.
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Reference: leeworks-agents/SPARC#1302
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