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molly-os-whitepaper
BoomJules/molly-os-whitepaper
molly-os-whitepaper is a machine learning model from BoomJules. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as cc-by-4.0.
Daniele Trovato - Core Labs R&D - v1.0 - June 2026
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Public
Updated Jul 18, 2026
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.pdf458 KB · 61%
At a glance
- License
- cc-by-4.0
- Access
- Public
- Created
- Jun 18, 2026
- Updated
- Jul 18, 2026
- SHA
- 8cc6cf95
Model card
From the Hugging Face model README
Molly OS - Whitepaper / Preprint
Daniele Trovato - Core Labs R&D - v1.0 - June 2026
Molly OS: A Model-Agnostic Inference Orchestration Layer for On-Device and Federated Inference.
A sovereign orchestration layer that routes each request across heterogeneous execution targets (on-device, LAN, cloud, external API), serves many domain-specialist LoRA adapters over a shared quantized base, enforces on-device-first data sovereignty, and continuously specializes via distillation. Evaluation across ~100 domains (neutral LLM judge, 115-panel probe) shows orchestration improves output quality over the unspecialized base.
Links
- Product: https://iamolly.ai
- Company: https://corelabsgroup.com
Read the paper
- On this page (renders with figures):
molly_os_whitepaper_en.md-molly_os_whitepaper_es.md-molly_os_whitepaper_it.md - PDF (offline / print, figures embedded):
molly-os-whitepaper-en.pdf - Branded rendered version (live): EN - ES - IT
Architecture figures are embedded as SVG in the .md views (fig_1.svg ... fig_5.svg)
and rasterized into the PDF. The 69 references are verified against the arXiv API, with
official venue links for the two non-arXiv works.
License
Status: PUBLIC preprint. This repository contains three artifact classes, each licensed separately:
| Artifact | License | What it allows |
|---|---|---|
| Whitepaper, translations & figures | CC-BY-4.0 | Share, quote, translate and build upon with attribution (incl. commercial) |
| Source code | Apache-2.0 | Use, modify and distribute, including commercially |
| Model adapters / weights | CC-BY-NC-4.0 | Share and adapt with attribution; no commercial use |
You may read, cite, quote, translate, and reuse the whitepaper with attribution. See
LICENSE. The orchestration service is the commercial product; for commercial use of
the adapter weights, contact [email protected].
How to cite
@techreport{trovato2026mollyos,
title = {Molly OS: A Model-Agnostic Inference Orchestration Layer for On-Device and Federated Inference},
author = {Trovato, Daniele},
institution = {Core Labs R&D},
year = {2026},
month = {6},
note = {Preprint, v1.0}
}
Contact (corresponding author): Daniele Trovato - Core Labs R&D - [email protected]
(c) 2026 Daniele Trovato / Core Labs R&D. Contact: [email protected]
- License
- cc-by-4.0
- Created
- Jun 18, 2026
- Updated
- Jul 18, 2026