nicklynberg/accelerated-intelligent-document-processing-on-aws
View on GitHub ↗Related repositories →This Guidance demonstrates a scalable, serverless approach for automated document processing and information extraction using AWS services, such as Amazon Bedrock Data Automation and Amazon Bedrock foundational models. It combines generative AI and optical character recognition (OCR) to process documents at scale.
active 2026-01-21 → 2026-04-28 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 98 days from 2026-01-21 to 2026-04-28. Pushes: 16 total, peak 3 in a day. Pull requests: 5 total, peak 1 in a day. Issues: 0 total, peak 0 in a day. Comments: 31 total, peak 11 in a day. Stars: 0 total, peak 0 in a day.
- Pushes
- Pull requests
- Issues
- Comments
- Stars
Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| alig4lfe | 42 | 10 | 4 | 14 |
| nicklynberg | 30 | 6 | 1 | 17 |
Recent activity
Latest issues, pull requests and releases
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.