The frequency of re-indexing a legal corpus depends on how often the data changes, the size of the corpus, and the performance requirements of your search system. For example, if your legal documents are updated daily (e.g., new court rulings, regulatory changes), re-indexing weekly or even daily might be necessary to ensure search results remain accurate. However, if the corpus is largely static—like a historical archive of past cases—re-indexing monthly or quarterly could suffice. The key is to align the schedule with the rate of data updates and user expectations for freshness.
Technical considerations also play a role. Re-indexing can be resource-intensive, especially for large corpora. If your system handles frequent updates, incremental indexing (updating only modified documents) might reduce overhead. For instance, a legal research platform adding 100 new case files daily could index those incrementally each night, avoiding full rebuilds. Monitoring tools like query latency metrics or index health checks (e.g., checking for missing documents) can signal when a full re-index is needed. If users report outdated results or slow searches, it’s a sign to re-evaluate your schedule.
Practical examples help illustrate this. A law firm tracking real-time legislative changes might re-index hourly using automated pipelines. In contrast, an academic legal database updated quarterly could re-index manually after batch imports. Hybrid approaches are also common: a court system might re-index nightly for routine updates but trigger a full rebuild after major statutory overhauls. Always test re-indexing in a staging environment to avoid downtime. For most teams, starting with weekly re-indexing and adjusting based on feedback strikes a balance between accuracy and resource use.