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rewrite org card prose: drop AI-tells, replace 'security veterans'
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README.md
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# Deep Fathom
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Base.
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This
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##
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[
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`ibm-granite/granite-4.1-8b`.
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of the base
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## How we build the models
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## Principles
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- **Security and compliance, intertwined by design.** Proof and
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protection, not bolted on after the fact.
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- **One truth, shared authority.** Same view across the team, the
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partner, and the assessor.
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## Who we work with
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- **C3PAOs and assessors** who need shared evidence, not screenshots.
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## Reach
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[deepfathom.ai](https://www.deepfathom.ai)
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for technical questions.
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# Deep Fathom
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Our mission is to make continuous CMMC readiness the norm for the
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Defense Industrial Base.
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Deep Fathom builds an AI-native compliance platform for CMMC. The
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platform takes on the routine work, tracks evidence as teams generate
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it, and keeps documentation aligned with the actual state of the
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controls. The people behind it are engineers and compliance
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practitioners who got tired of treating audits as ceremony.
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This Hugging Face org is the open side of that work. We publish the
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ML pieces we can release: model adapters today, datasets later when
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licensing allows.
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## What's here
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[basalt](https://huggingface.co/deepfathom/basalt) is the only public
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artifact right now. It is a LoRA adapter for CMMC, NIST SP 800-171,
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and DFARS practitioner Q&A, layered on `ibm-granite/granite-4.1-8b`.
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The repo is private through M-Train v1 validation. Public release
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depends on eval results and a license review of the base model and
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corpus terms.
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## How we build the models
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We choose curation over scale. Roughly 13,000 judge-validated
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practitioner pairs do better work than 100,000 unfiltered scrapes
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when the domain is this narrow.
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Every artifact links back to a reproducible training run. We record
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the data version, seed, hyperparameters, and judge configuration so a
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later release can be checked against the artifact it claims to
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supersede.
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We publish LoRA adapters rather than merged weights. PEFT and vLLM
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load the base and the adapter together at runtime. The result is the
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latest upstream base, our specialty layer composed on top of it, and
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the option to swap each layer independently.
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## Principles
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1. More rigor. Radically less effort.
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2. Frontier AI, applied where it carries weight.
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3. Security and compliance treated as one workflow.
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4. One truth, shared across the team, the partner, and the assessor.
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## Who we work with
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Defense contractors and DIB suppliers, including the small businesses
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that CMMC was always going to test hardest. MSPs and MSSPs that
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deliver compliance services for clients. C3PAOs and assessors who
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want shared evidence instead of screenshots.
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## Reach
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[deepfathom.ai](https://www.deepfathom.ai). Use model repo
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discussions for technical questions.
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