Early Access — Now Open Patent Pending 100% Lossless

Compression that
actually compresses.

AhanaZip is AI-native lossless compression. Up to 87.97% smaller on text — a 13-point leap over zstd‑22. Drop-in replacement. SHA‑256 verified.

0%
Compression on text
+0 pp
Better than zstd‑22
0%
On scientific data
SHA-256 verified · Free tier available · No credit card required · API access at launch
vs. today's standards
gzip lv9 ~68% smaller
Brotli lv11 ~70% smaller
zstd‑22 ~75% smaller
AhanaZip up to 99% smaller ✦
The Problem

Your compression stack
is from 1992.

gzip, zstd, and Brotli are all built on the same idea: find repeated byte sequences and replace them with shorter references. They have no concept of what your data means.

A transformer-based neural model can predict the next byte in a log file, a JSON response, or a legal document with far greater accuracy than any pattern-matching heuristic. That predictive power directly translates to fewer bits — approaching the theoretical information limit.

1992
gzip — DEFLATE algorithm. LZ77 + Huffman coding. State of the art for its era.
1994
zlib — Same core algorithm. Still the default in Python, Docker, HTTP.
2013
Brotli — Google's improvement. Better, but still statistical byte-pattern matching.
2016
zstd — Facebook's answer. Faster. Still no semantic understanding of data.
2026
AhanaZip — Byte-level transformer + arithmetic range coder. Approaches the entropy limit.
How It Works

Three layers. One quantum leap.

Step 01
🧠
Neural probability model
A trained byte-level transformer (5M–200M params) builds a probability distribution over the next byte in your data stream, conditioned on context up to 4,096 bytes back.
Step 02
⚙️
Arithmetic range coder
A 64-bit arithmetic range coder encodes each byte using the model's probability estimate. Highly probable bytes consume near-zero bits. Total output approaches the theoretical Shannon entropy limit.
Step 03
🔒
Verified .aarm container
Output is sealed in the .aarm universal container — versioned, self-describing, and SHA-256 verified. Decompression is lossless by construction. Silent corruption is impossible.
Benchmarks

Real numbers. Reproducible. Audited.

All benchmarks run on standard corpora with published methodology. Every result includes full parameter logs. SHA-256 hash of every compressed file verified on decompress.

AhanaZip
87.97% +13.24 pp
zstd‑22
74.73% baseline
Brotli lv11
~70.5% −4.2 pp
gzip lv9
~67.6% −7.1 pp

† Measured on enwik8 (100MB Wikipedia text). AhanaZip nano model, 5.25M parameters, BPE tokenizer. zstd, Brotli, gzip run at maximum compression level. All methods strictly lossless. Full methodology at api.ahanazip.com/docs/benchmarks.

Domain-Specialist Models

Fine-tuned on domain corpora, specialist models push compression ratios dramatically higher on structured data. The same base model, specialized in 5,000–8,000 training steps.

🔬
Scientific papers
99.10%
vs 74.73% zstd-22
⚖️
Legal documents
98.74%
vs 74.73% zstd-22
📡
IoT / sensor data
95.98%
vs ~65% zstd-22
🏥
Medical records
91.52%
vs 74.73% zstd-22
💹
Financial data
91.16%
vs 74.73% zstd-22
🌐
Network packets
86.99%
vs 74.73% zstd-22
For Developers

One line to switch.
Zero rewrites.

AhanaZip mirrors the API surface of gzip and zstd. Replace your current compressor in one line. The REST API accepts binary and returns binary — language agnostic.

📦
pip install ahanazip
Drop-in Python library. compress(data) / decompress(data) — that's it.
🌐
REST API
POST bytes, receive bytes. Works from any language. Python, Node.js, Go, Rust, curl. SDKs at GA.
⚡
Free tier — no credit card
5 requests/day free forever. Enough to evaluate on your production data before you pay anything.
🔑
Open benchmarks
Every benchmark is reproducible. Full JSONL logs, SHA-256 hashes, parameter files. No black-box claims.
Python 
# Before — standard zstd
import zstandard as zstd
cctx = zstd.ZstdCompressor(level=22)
compressed = cctx.compress(data)

# After — AhanaZip (one line change)
import ahanazip as zstd
cctx = zstd.Compressor()
compressed = cctx.compress(data)

# REST API (any language)
import requests

resp = requests.post(
  "https://api.ahanazip.com/v1/compress",
  headers={"X-API-Key": api_key},
  data=open("archive.log", "rb")
)
compressed = resp.content  # .aarm bytes

# Verify lossless integrity
original = ahanazip.decompress(compressed)
# SHA-256 checked automatically ✓
🖥️
CLI available
ahanazip compress file.log → file.log.aarm
For Engineering Teams

Your storage bill has an obvious fix.

At scale, compression ratio is money. A 13-point improvement over zstd doesn't sound like much until you're storing petabytes.

💾
Storage cost reduction
Application logs, JSON telemetry, and database backups compress dramatically better with domain-tuned models. Less data stored = lower S3, GCS, and Azure bills.
10TB of logs → ~1.2TB with AhanaZip
⚡
Faster data transfer
Smaller payloads mean faster API responses, reduced egress bandwidth, and fewer cache misses. The ratio improvement compounds at every network hop.
~3× smaller than gzip on JSON APIs
🔒
Integrity by default
Every .aarm file contains the SHA-256 of the original. Decompression fails loudly on corruption rather than returning silently corrupted data.
Zero silent-corruption incidents possible
🏗️
Drop-in migration
AhanaZip mirrors the gzip and zstd API surface. No pipeline rewrites, no migration risk. Run side-by-side, compare ratios, switch when confident.
One-line change to existing pipelines
🧩
Custom domain models
Enterprise plans include fine-tuned specialist models trained on your data types: logs, financial data, scientific records — each getting domain-optimized ratios.
Up to 99.10% on scientific corpora
📋
Audit-ready
Every compression operation is logged with input hash, output hash, model version, and compression ratio. SOC 2 compliance roadmap in Q3 2026.
Full JSONL audit trail on Enterprise
Pricing

Early access is free.

Waitlist members get 90 days of Pro access free at launch. No credit card now.

Free
$0/mo
No credit card. Forever free tier.
  • 5 API requests / day
  • Up to 10MB per file
  • Nano model (5.25M params)
  • SHA-256 verification
Pro
$29/mo
Waitlist members get 90 days free.
  • 10,000 API requests / month
  • Up to 2GB per file
  • Micro model (27M params) — better ratios
  • All 12 domain specialists
  • Python SDK + CLI
Enterprise
$299/mo
Custom contracts available.
  • Unlimited requests
  • Medium model (201M params) — maximum ratios
  • Custom domain fine-tuning on your data
  • Full audit trail (JSONL) + SLA
  • Dedicated Slack + onboarding
FAQ

Common questions

Yes — 100% bit-perfect. Every decompressed byte is guaranteed identical to the original. The .aarm container embeds a SHA-256 digest of the original data, and the decompressor verifies it before returning any bytes. Decompression will throw an explicit error if integrity fails — there is no silent corruption path.
Compression is GPU-accelerated via the API and runs at 50–200 MB/s depending on model size. Decompression is significantly faster — the range decoder runs CPU-only and scales to 500 MB/s. AhanaZip is designed for archival, backup, and batch compression workloads rather than real-time streaming (for which zstd-1 remains the right tool).
Yes, but ratios will vary. AhanaZip's largest gains are on patterned data: text, JSON, logs, source code, structured records, and domain-specific formats. On already-compressed binary (JPEG, MP4, ZIP), the model gains little over zstd. The API will automatically fall back to zstd for data types where the neural model doesn't improve on it.
AhanaZip's core algorithm — BPE-guided neural arithmetic coding with the Fractal Entropy Tokenizer — has been filed with the USPTO (pending). This does not affect your ability to use the API or SDK under the standard commercial license. It means competitors cannot copy the algorithm without a license. Enterprise customers receive a perpetual-use license as part of their contract.
We're targeting Q2 2026 for the public API launch. Early access members will receive API keys before the public launch, 90 days of Pro access at no charge, and direct input into the SDK design. You'll be notified by email as soon as your access is ready — no action needed from you after signing up.

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