PUCE2026-05-106 min read
PUCE Engine — Intelligent ML Compression
How the PUCE compression engine uses machine learning to automatically select the optimal algorithm per data block.
The PUCE Engine analyzes each data block and extracts 20 features (entropy, runs, n-grams, compressibility) using JIT-optimized functions with Numba, achieving throughput above 2 GB/s.
Based on these features, an ML model automatically selects the optimal compression algorithm: ZSTD for structured data, LZ4 for low latency, Brotli for text, or LZMA for archival.
This approach is particularly effective in enterprise backups, where different data types (SQL, logs, binaries) coexist in the same stream.