Hi HN, I’m building SEE (Semantic Entropy Encoding): a searchable compression format for JSON/NDJSON. Goal: reduce the “data tax” (storage/egress) and “CPU tax” (decompress/parse) by keeping JSON searchable while compressed, with page-level random access.

I just published a proof-first evaluation release:

Offline DEMO ZIP (~10 min): prints compression ratios + skip rates + lookup latency (p50/p95/p99)

DD pack: audit/repro evidence (decode mismatch=0, extended mismatch=0, audit PASS)

Latest release: https://gitlab.com/kodomonocch1/see_proto/-/releases

Direct DEMO ZIP: https://gitlab.com/api/v4/projects/79686944/packages/generic...

OnePager is included in the release assets.

I’d love feedback on:

what workloads you’d try this on, and

what integration path would make this compelling vs Zstd + external indexing.