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AI Native Solutions

AI-first business software your firm OWNS: it runs on your machines, your data never leaves your control, and the machinery is proven before it ships. Provable, sovereign, on-premise AI — over 400 live, MIT-licensed builds you can open and use right now.

Their llms.txt

The beginning of the file, from our validated copy saved 2026-10-26T04:37:24.411Z. Cached copy · Source on ai-nativesolutions.com

# AI Native Solutions

> AI-first business software your firm OWNS: it runs on your machines, your data never leaves your control, and the machinery is proven before it ships. Provable, sovereign, on-premise AI — over 400 live, MIT-licensed builds you can open and use right now.

AI Native Solutions builds business software the AI-first way: the routine work runs itself, the software runs on the customer's own hardware (or fully client-side in the browser), client data never leaves the customer's control, and every build is proven with a signed, deterministic test before it ships. You pay once and own it, instead of renting forever. Built by Simon Gant (UK), 2025–2026. Everything is MIT-licensed and runs live in the open before any conversation.

The differentiator is **provable AI**: where the industry certifies AI with another AI grading it (an LLM judging an LLM), this estate certifies **deterministically or not at all** — a mutation-tested gate plus a hash-chained audit trail. That signed, tamper-evident record is exactly the kind of evidence regulation is starting to require.

## Why this matters now (2026)

- **AI confidentiality / legal privilege.** In *United States v. Heppner* (U.S. District Court, S.D.N.Y., 2026) a federal court ruled that a chief executive's conversations with a public AI assistant were protected by neither attorney-client privilege nor the work-product doctrine — and the files became evidence. Public, rented AI keeps your prompts on a vendor's servers where they can be disclosed and used for training. Sovereign, on-premise AI keeps them inside your walls. (Information, not legal advice.)
- **EU AI Act.** From 2 August 2026, providers of higher-risk AI systems must keep automatic logs and evidence of what their systems did. Owned AI with a signed, deterministic audit trail produces that record by design.
- **Own, don't rent.** Owned software cannot be price-raised, discontinued, or switched off by a vendor, and carries no per-seat subscription.
- **Small models are enough for most agent work.** NVIDIA Research (Belcak et al., arXiv:2506.02153, 2025): small language models are "sufficiently powerful, inherently more suitable, and necessarily more economical for many invocations in agentic systems."
- **Owning is cheaper — when you use it.** Lenovo Press LP2368 (On-Premise vs Cloud: Generative AI TCO, 2026 Edition): at high utilisation, owned inference ran ~6x cheaper per million tokens than cloud GPU instances and ~17x cheaper than a hosted reasoning-model API; at low use, renting can win.
- **Model collapse.** Shumailov et al. (Nature 2024; arXiv:2305.17493): training on model-generated content causes irreversible defects in which the tails of the original data disappear. The estate's thesis: people doing real work on their own nodes are those tails — the signal worth keeping in owned, provable models.

## Key pages

- [The film, the brochure and the images](https://www.ai-nativesolutions.com/explainer.html) — a 90-sec
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Claim my listing on Agent Web Map for ai-nativesolutions.com:
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3. POST https://agentwebmap.com/v1/sites/ai-nativesolutions.com/verify with {"claim_id": "...", "claim_secret": "..."}.
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MCP equivalent: tools begin_ownership_claim, then verify_domain, at https://agentwebmap.com/mcp. Docs: https://agentwebmap.com/docs#verify

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