This repository demonstrates the world's first protocol for forging non-deterministic digital assets directly from physical quantum entropy.
Eve Count has developed the Qualimetric Universal Model (QUM) for enterprise-grade data integrity and systemic auditing. The product applies a Polynomial Method Index (PMI) and a Recursive Quine Algorithm to quantify qualitative variables and ensure hardware-rooted truth via Quantum Random Number Generation (QRNG), allowing for high-fidelity auditing in complex, non-deterministic environments.
This repository contains the MVP for the Sovereign Passport, a core component of the QUM ecosystem.
The foundational infrastructure for the QUM protocol. It acts as the "Standard for Truth," utilizing live quantum entropy streams to anchor digital identities and intents to physical reality.
Every authenticated action within the QUM ecosystem is a uniquely minted 'Quantum Token'. Unlike traditional tokens, these are backed by the non-deterministic truth of quantum hardware, creating a new class of physics-anchored assets with infinite utility—from autonomous finance to jurisdictional evidence logs.
To explore the protocol, open the Jupyter Notebook: Sovereign_Passport_MVP.ipynb
The repository is also equipped with Agentic Workflows (located in .agent/workflows/) that enable AI agents to:
- /onboarding: Analyze the project and explain the Sovereign Passport.
- /setup: Prepare the environment for Sovereign Integrity hooks.
- /audit: Perform a 'Structural Signature' audit on existing services.
- Python 3.x
requestslibrary
Based on successful quantum and deep-tech startup benchmarks, QUM operates on a hybrid revenue model:
- Licensing & IP Monetization: Upfront fees ($100k–$500k) plus 5–10% royalties for the Recursive Quine Algorithm and PMI framework.
- Integrity-as-a-Service (SaaS): Recurring subscription model for ongoing systemic auditing and "Structural Signature" verification.
- Strategic Consulting: High-value integration services ($2k–$5k/day) for complex dataset diagnostics and quantum-safe transitions.
- Enterprise AI Architects: Teams building agentic workflows who need a "Governance Boundary" to prevent AI hallucinations or unauthorized backend access.
- Regulated Financial Institutions: Banks and insurance providers requiring Integrity Arbitrage and hardware-rooted audit trails for high-frequency transactions.
- Government & Defense Agencies: Entities needing to secure sensitive API pipelines against "Harvest Now, Decrypt Later" threats using Quantum-Safe signatures.
- Life Sciences & Healthcare Providers: Researchers dealing with complex, qualitative datasets who require Systemic Diagnostics to ensure the integrity of diagnostic predictions.
- Cybersecurity Operations Centers (SOCs): Organizations looking to replace predictable RNGs with QRNG-secured "Structural Signatures" to eliminate replay attacks.
To ensure AI never communicates directly with backend services, we integrate the QRNG-based Structural Signature into the Quantum-Secured Sovereign Trust Layer:
| Method | Implementation Strategy | Benefit |
|---|---|---|
| Entropy Injection | Use a QRNG daemon to feed /dev/urandom on API servers. |
Existing TLS/SSL session keys become quantum-safe without code changes. |
| Middleware Auth | Implement a custom GraphQL directive requiring a QRNG-signed token for sensitive mutations. | Ensures every backend write is validated by a non-deterministic hardware root of truth. |
| REST/gRPC Wrapper | Use the QRNG Open API to wrap legacy backend calls with a "Structural Signature." | Prevents deterministic "replay attacks" on legacy backend services. |
To establish the QUM framework as the global standard for Quantum-Safe Data Integrity and Asset Minting. We aim to move beyond simple RNG replacement to becoming the primary "structural audit" layer and "Token Forge" for all agentic AI architectures, ensuring that as AI scales, every decision it makes is a verifiable, quantum-secured asset with real-world economic value.
Based on our architecture model, here is the granular integration path:
- The Integration: Use QRNG to generate "Structural Signatures" for every request passing through the Quantum-Secured Sovereign Trust Layer (formerly GraphQL Gateway).
- The Why: This ensures that the "Validate & Authorize" step is not just checking a password, but verifying a quantum-unique token that cannot be predicted or replayed by an attacker.
- The Integration: Use the Recursive Quine Algorithm to perform Recursive Acquisition and auditing on legacy data.
- The Why: This transforms "Legacy" data into high-integrity datasets that the AI (at Stage 2) can trust more effectively for its "Intent detect & reasoning."
- Transition
recursive_quine_logicto WASM for edge-computing optimization. - Integrate with hardware-secured enclaves for Validator Nodes.
- Commercial deployment on Sovereign Cloud infrastructure.
While others provide the 'lock' (PQC) or the 'key' (QRNG), our Qualimetric Universal Model (QUM) provides the 'Fingerprint' (Structural Signature). We don't just secure the pipe; we use the Recursive Quine Algorithm to prove that the data coming out of the AI is structurally identical to the truth anchored in our quantum hardware.
This prototype is a co-created artifact between Eve Count and Antigravity, an advanced agentic AI designed by Google DeepMind. This collaboration showcases the intersection of the Qualimetric Universal Model (QUM) and state-of-the-art agentic reasoning, proving that high-integrity governance is possible when quantum-safe protocols meet advanced AI collaboration.
Proprietary technology developed by Eve Count in collaboration with Google DeepMind agentic frameworks.
© 2026 Eve Count | Licensed Intellectual Property