Early Access — Now Open Patent Pending 100% Lossless

Compression that
actually compresses.

AI-native lossless compression — up to 86% smaller, 186× faster than zstd, SHA‑256 verified. Drop-in replacement for gzip and zstd.

0%
Lossless compression
0 MB/s
Turbo encode speed
0%
On scientific data
Or try the live demo — no signup needed
SHA-256 verified · Free tier available · No credit card required · API access at launch

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.

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.

Every byte of patterned data is an opportunity.

AhanaZip’s neural model understands the structure of your data. The more repetitive and semantic the content, the bigger the gains.

📜
Application logs
Structured log lines — timestamps, levels, trace IDs — are highly repetitive. AhanaZip’s model exploits that repetition to near-entropy limits.
~88% on text logs
📦
JSON API responses
Repeated field names, consistent value types, and predictable schema structure make JSON ideal for neural compression. Compress before caching or storage.
~3× smaller than gzip
🗂️
Database backups
SQL dumps, CSV exports, and Parquet files all benefit from domain-aware compression. Store more history on the same S3 budget.
Up to 55% smaller than zstd
🧬
Scientific data
Research papers, genomic sequences, and sensor readings contain deep long-range correlations a 4,096-token context window captures perfectly.
99.10% on science corpora
⚖️
Legal & compliance docs
Contracts, filings, and audit trails are dense with repeated boilerplate. Specialist models compress them 25× smaller than raw text while preserving every byte.
98.74% on legal text
🐈
Source code archives
Code repositories have predictable identifiers, keywords, and patterns. AhanaZip is ideal for archiving large monorepos and build artifact caches.
~85% on Python/JS source

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 (Lossless)
86.35% +16.8 pp
zstd‑22
69.5% baseline
Brotli lv11
~72.0% −14.4 pp
gzip lv9
~62.2% −24.2 pp

† Measured on enwik8 (10 MB) Wikipedia corpus. AhanaZip Lossless mode vs zstd-22, Brotli-11, gzip-9 at maximum compression level. All methods strictly lossless. SHA-256 verified on every result. Full methodology at api.ahanazip.com/docs/benchmarks.

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 69.5% zstd-22
⚖️
Legal documents
98.74%
vs 69.5% zstd-22
📡
IoT / sensor data
95.98%
vs ~65% zstd-22
🏥
Medical records
91.52%
vs 69.5% zstd-22
💹
Financial data
91.16%
vs 69.5% zstd-22
🌐
Network packets
86.99%
vs 69.5% zstd-22

Not just a ratio gain.

AhanaZip closes fundamental capability gaps that gzip, Brotli, and zstd have never addressed.

Capability gzip Brotli zstd AhanaZip ✶
Semantic data understanding
Domain-specialist fine-tuning
100% lossless
SHA-256 integrity on every file
Context-aware (long-range patterns) Limited 4,096 ctx
REST API out of the box
Full JSONL audit trail
Approaches Shannon entropy limit

Better compression.
Up to 186× faster.

Real benchmark numbers — enwik8-64MB Wikipedia corpus, same hardware. Ratio panel shows AhanaZip Lossless vs competitors at max compression. Speed panel shows AhanaZip's three lossless modes — all produce bit-perfect SHA-256 verified output.

Compression ratio — how much smaller? (higher is better)
AhanaZip Lossless ★ best 86.35%
Brotli-11 72.0%
zstd-22 69.5%
gzip-9 62.2%
Encode throughput — MB/s (higher is faster)
AhanaZip Turbo ★ fastest 745 MB/s
AhanaZip Fast 110 MB/s
gzip-9 ~20 MB/s
zstd-22 (max) ~3 MB/s
AhanaZip
gzip-9
Brotli-11
zstd-22

* enwik8 (10 MB) Wikipedia corpus, 24-core machine. Ratio: AhanaZip Lossless (best-ratio mode) vs codecs at max compression, all lossless. Speed: AhanaZip Turbo and Fast modes vs gzip-9 and zstd-22 at max compression (~3 MB/s). All AhanaZip modes produce bit-perfect output with SHA-256 integrity verification. Specialist domain models achieve higher ratios on structured corpora (scientific, medical, financial).

Drop a file. Get real numbers.

Any file type, up to 50 GB. Files ≤2 MB compress live and download instantly. Larger files are sampled for accurate projections — no signup, no tracking, no upload wait.

File 1
Drop file here
or click to browse
Up to 50 GB  ·  any file type
File 2
Drop file here
or click to browse
Up to 50 GB  ·  any file type
Zero tracking. Zero storage. Your files are read locally in your browser, a small representative sample is sent over HTTPS to our API, and the result is returned immediately — nothing is saved, logged, or retained. We collect no file names, no contents, no metadata. No cookies. No fingerprinting. No analytics on your data. Read the API privacy policy →

Rate-limited to 5 free requests/IP/day for live compression. For unlimited batch compression of large files, join the waitlist for Pro early access.

Paste text. See the difference.

Paste JSON, logs, or source code and compress it live. See ratio, speed, and byte-level stats in real time. 5 free requests/day — no key needed.

api.ahanazip.com / v1 / compress / text
Samples 0 bytes
Input — paste any text
Response headers
Hit Compress to see live stats…

X-ACP-Savings-Pct: —
X-ACP-Ratio: —
X-ACP-Original-Size: —
X-ACP-Compressed-Size:—
X-ACP-Duration-Ms: —
X-ACP-Tier: free
Size saved
Ratio
Original
Compressed
Time

Rate limited to 5 free requests per IP per day.   Join the waitlist for 90 days of Pro access free at launch.

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

Your storage bill has an obvious fix.

At scale, compression ratio is money. A 17-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 → ~1.4TB 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

📊 Storage savings calculator

Drag the sliders to estimate your annual cost reduction — before you pay a cent.

50 TB
$23/TB
$0
Annual savings
0 TB
Storage freed/year
ROI vs. Pro plan ($29/mo)

Simple, transparent pricing.

Start free with generous limits. Upgrade when you need more power. No hidden fees.

Free
$0/mo
No credit card required. Always free.

  • 5 API requests / day
  • Up to 10 MB per file
  • Nano model (5.25M params)
  • SHA-256 verification
Pro
$29/mo
Free for 30 days — no credit card required to start.

  • 10,000 API requests / month
  • Up to 2 GB per file
  • Micro model (27M params)
  • SHA-256 verification
  • Email support
Paid billing is processed securely by Stripe.
Enterprise
Custom
For organizations with advanced needs.

  • Unlimited API requests
  • No file size cap
  • Dedicated infrastructure
  • Custom fine-tuning on your data
  • JSONL audit trail + SLA
  • Dedicated Slack support
Enterprise subscriptions and invoices are managed via Stripe.
Enterprise & OEM
Contact Us
Custom pricing tailored to your organization.

  • Unlimited requests + petabyte scale
  • On-prem model deployment
  • OEM / embed license (revenue share)
  • 99.9% uptime SLA + dedicated infra
  • Executive onboarding & CSM

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 110–745 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.

Be first.
Compress better.

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