Worked Examples

Three worked examples of how we approach AI sovereignty, Zero-Knowledge private AI, and post-quantum cryptography — the kind of reference architecture an engagement produces, written out in full so you can judge the method before you buy it.

Enterprise AI Sovereignty

Aegis365 | Prompt-Layer Governance | Zero-Knowledge

Worked Example 01: Enterprise AI Sovereignty

The Threat: A global enterprise faced critical IP exfiltration risks as developers routinely pasted proprietary algorithms into public LLMs. Traditional DLP and SIEM tools were completely blind to these HTTPS payloads.

The Architecture: We engineered and deployed an 8-layer interception pipeline via a Hybrid Sidecar model. Utilizing local Small Language Models (SLMs) for intent analysis, we established prompt-level enforcement that detects and classifies source code, PII, and financial data. By applying format-preserving tokenization, the LLM receives a coherent synthetic prompt, ensuring the enterprise's true IP never leaves the perimeter in plaintext.

Execution Highlights
  • Sub-50ms deterministic Agent Action Schema evaluation.
  • Strict Sole-Custody Prohibition using HSM multi-approver quorum.
  • Immutable, tamper-evident cryptographic audit ledger.

BrainNest365 | Local LLM Orchestration | GraphRAG

Worked Example 02: Zero-Knowledge Private AI

The Threat: Standard enterprise AI deployments require sending highly sensitive internal corpora to external providers for indexing, breaking data residency and privacy mandates.

The Architecture: We designed a fully air-gapped, sovereign AI ecosystem operating on local infrastructure. We orchestrated a dual-store retrieval system: Qdrant indexing native 4096-dimensional embeddings alongside PostgreSQL for relational structures. The system utilizes Microsoft GraphRAG to harvest complex entity relationships, executing all inference and embedding locally without a single outbound API call to a third-party LLM.

Execution Highlights
  • 100% local inference ensuring zero conversation or document leakage.
  • Dual-write consistency between vector ANN indexes and relational databases.
  • Transparent match scoring and contradiction tracking via semantic memory.
Zero-Knowledge Private AI
Post-Quantum Cryptography

QuantumReady 365 | FIPS 203/204 | Crypto-Agility

Worked Example 03: Post-Quantum Cryptography

The Threat: The "harvest-now, decrypt-later" threat model means long-lived enterprise secrets protected by RSA and ECC are already compromised by future cryptographically-relevant quantum computers.

The Architecture: We developed a comprehensive migration framework transitioning .NET 10 infrastructure to NIST-standardized algorithms, specifically ML-KEM and ML-DSA. Instead of a disruptive "flag day," we implemented a hybrid key exchange and a crypto-agility envelope. This allows systems to run classical and post-quantum cryptography simultaneously, wrapping AES-256 data-at-rest keys with ML-KEM to secure data without touching the underlying symmetric cipher.

Execution Highlights
  • Implementation of FIPS 203 (ML-KEM) and FIPS 204 (ML-DSA) standards.
  • Automated Cryptographic Bill of Materials (CBOM) generation.
  • Self-describing, versioned envelopes for seamless algorithm rotation.

About these examples

The three examples above are illustrative scenarios, not delivered client engagements. They are written out in full to show the method — how we frame the threat, what architecture we would propose, and which trade-offs we would make. We would rather you judge the reasoning than take a testimonial on trust.

Client work runs under strict Non-Disclosure Agreements and is delivered through NestVault365, our zero-knowledge data room. Where a real engagement is ever published here, it will be labelled as one and published with the client's written consent.

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