Add cloudsealed-jit to Data Analysis

[cloudsealed]

cloudsealed-jit is a JIT-compiled Python library for streaming anomaly detection and MAD profiling, built for FinOps cost anomaly detection and SRE telemetry pipelines.

Why it belongs here

• Fills a gap: no current entry for streaming anomaly detection under Data Analysis. Closest alternatives (PyOD, scikit-learn) are batch-only and heavyweight.
• Active: 5 releases on PyPI (latest 0.4.2), Apache 2.0, documented quickstart and benchmarks.
• Specific use case: AWS/GCP/Azure billing anomaly detection — a recurring need not addressed by any current entry.

Checklist

• Repository has a clear README with quickstart
• Open source (Apache 2.0)
• Short description focused on what it does, not marketing
• Linked to the GitHub repo

[JinyangWang27]

@cloudsealed thanks for your submission. However, Data Analysis covers general dataframe libraries, so a domain-specific anomaly-detection tool doesn't fit there. The package is also marked Beta on PyPI, and the list only takes production-ready projects. See CONTRIBUTING.md.