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title: README
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# Broadnet Technologies
**Enterprise AI that actually works. Built and run on our own infrastructure.**
We run our own inference for Arabic and English businesses and publish what we measure, under our own name, with a DOI on every
paper. Every model here comes with the paper and the evidence behind its numbers.
- **Gemma 4 26B A4B Uno pilot adapter** — the first Uno adapter for a mixture-of-experts model, lossless, with its serving profile and
measurements on the card. Paper: [10.5281/zenodo.22820511](https://doi.org/10.5281/zenodo.22820511).
- **Uno for vLLM** — self-drafting speculative decoding with no separate draft model, validated on Ampere, Hopper and Blackwell.
Code and container: [github.com/brntech/vllm-uno](https://github.com/brntech/vllm-uno).
- **Uno in vLLM** (Qwen3-8B), the dense-target study: [10.5281/zenodo.22652609](https://doi.org/10.5281/zenodo.22652609).
- Sensitive-data safety: [The Safety Map](https://doi.org/10.5281/zenodo.19688431), 39 models from 14 labs.
Inference API: [inference.broadnet.ai](https://inference.broadnet.ai) · Research: [broadnet.ai/research](https://www.broadnet.ai/research)
Also from Broadnet: [DialerBee](https://dialerbee.com), the AI outbound dialer with answering-machine detection in 11 languages, and
[broadnet.me](https://www.broadnet.me), our telecom and omnichannel messaging (bulk SMS, A2P, HLR lookup, SMS firewall).
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