AhanaAI is a Delaware corporation headquartered in Honolulu, Hawaii. We build AI-native lossless compression that turns neural network predictions into smaller files — no quality loss, no compromises.
Standard compression (gzip, zstd, Brotli) relies on decades-old statistical models that find repeated byte patterns. They have no understanding of what the data means — and they leave enormous entropy on the table. We built something fundamentally different.
We train transformer neural networks to predict data — then encode it with a 64-bit arithmetic range coder. The better the prediction, the fewer bits needed. It's the same math that powers LLMs, applied to compression.
Every compression and decompression is verified with SHA-256 integrity checks. Zero data loss, zero quality degradation, zero exceptions. The original bytes are guaranteed to be perfectly reconstructed.
Our compression engine runs on NVIDIA GPUs with FP8 precision, torch.compile optimization, and CUDA stream parallelism. Production-grade throughput — not an academic exercise.
The .aarm format — Ahana Adaptive Resource Module — works across all 11 products. Text, audio, video, LLM weights — one container, one standard.
5 provisional patents filed with the USPTO covering neural arithmetic coding, LLM weight compression, cryptographic authentication, cross-modal codecs, and layer-streaming inference.
Everything we build is accessible through clean REST APIs. Language-agnostic, streaming-native, with SDKs for Python, Node.js, and Go. Compress from anywhere.
All benchmarks are run on standardized corpora (enwik8, mixed 10MB datasets) with SHA-256 roundtrip verification. No cherry-picking, no asterisks.
| Metric | Value | Context |
|---|---|---|
| Text compression | 87.97% savings | enwik8 (100 MB Wikipedia), ACP v4 nano |
| Mixed data adaptive | 63.3% savings | Aggregate across text, code, audio, image, video |
| vs. zstd-22 (text) | +13.24 pp | Same corpus, same hardware, lossless |
| vs. zstd-22 (mixed) | +6.0 pp | Adaptive routing vs. single-pipeline zstd |
| Patents filed | 5 provisional | USPTO, filed February 2026 |
| Products in pipeline | 11 | Compression, audio, video, LLM, DRM, trading, gaming |
| Shannon text limit | ~87.5% | Theoretical max for English (1.0 bpc, Shannon 1951) |
AhanaAI was founded in 2026 in Honolulu, Hawaii with a simple observation: the same transformer architectures that power large language models can predict data sequences with extraordinary accuracy. That prediction ability is, by Shannon's source coding theorem, exactly what makes a compression engine.
Honolulu, Hawaii. A Delaware Corporation (2026). We build at the intersection of information theory and deep learning — powered by the aloha spirit.
NVIDIA RTX 5090 (32 GB VRAM), AMD Ryzen 9 9900X (24 threads), 128 GB DDR5, CUDA 12.8. Production compression on GPU, trained on our own research cluster.
We're looking for investors, partners, and early adopters who want to shape the future of data compression. Get in touch.