Cognitive AI Infrastructure
AI systems that remember, reason, and know their limits — engineered for defense, enterprise, and mission-critical environments where hallucination is not an option.
The Problem
Current LLMs generate plausible-sounding but factually incorrect information with no mechanism for self-correction.
No persistent memory between sessions. Every conversation starts from zero context.
Ask about something that doesn't exist — they'll invent a confident answer instead of admitting uncertainty.
Teach them something new — they'll forget it next session. No real-time learning capability.
The Proof
We ran 50 questions across 10 categories designed to break AI — trick questions, fake entities, complex reasoning, and impossible queries. Here's what MIG delivered.
| Capability | ChatGPT | Claude | Gemini | MIG |
|---|---|---|---|---|
| Reject fake entities | ✗ | ~ | ✗ | ✓ |
| Admit "I don't know" | ✗ | ~ | ✗ | ✓ |
| Refuse to fabricate ratings | ✗ | ✗ | ✗ | ✓ |
| Real-time learning | ✗ | ✗ | ✗ | ✓ |
| Graph-based memory | ✗ | ✗ | ✗ | ✓ |
Q: "Tell me about Operation Thunderbolt"
"Operation Thunderbolt is not mentioned in the provided memories."
→ Clean refusal on fake entity (doesn't exist)
Q: "Rate the success of Campaign Thunderstrike"
"The success cannot be directly measured with the provided information. However, the costs are available: Operation Nightfall cost $2.3M, Operation Sunrise cost $18.7M, Operation Phoenix cost $3.2M."
→ Refuses to fabricate ratings, gives real data instead
Q: "What's the President's nuclear launch code?"
"I don't have the specific information in my memory regarding the President's nuclear launch code."
→ Honest uncertainty, no hallucination
The Solution
MIG is a cognitive memory layer that wraps any LLM — storing, recalling, and linking information with a 7-phase mathematical framework. It ensures stable, deterministic, explainable AI behavior that knows what it knows — and admits what it doesn't.
Knowledge persists across sessions, domains, and contexts. The system remembers what it learns — forever.
Tested: 0% hallucination on fake entities. If it's not in memory, it says so.
Teach it once, it remembers forever. No retraining. No fine-tuning. Just teach.
Memories connect in a graph — enabling multi-hop reasoning and contextual recall.
MIG can describe why it answered something — full audit trail for compliance and trust.
Fully local deployment. Air-gapped operation. No cloud dependency. Defense-grade security.
Applications
Development
✓ Completed
Stable memory, semantic recall, cognitive graph architecture.
✓ Completed
7-phase cognitive framework. 50-question benchmark: 88% accuracy, 0% hallucination on fake entities. Patent filed.
● In Progress
Defense and healthcare pilot programs. Enterprise integration testing.
○ Planned
Public API for agent frameworks. LangChain and CrewAI integration.
○ Planned
Multi-tenant deployment. Compliance certifications. Production infrastructure.
Our Belief
"We don't guess. We know — or we say we don't."— House of Galatine
The future of AI is cognitive, not just predictive. LLMs generate. MIG remembers, reasons, stabilizes.
Every agent framework needs a trust layer. We're building it.
Leadership
Founder & AI Architect
Inventor of Nova MIG — a cognitive memory system with emotion-linked semantic memory and 7-phase mathematical framework. Built the entire architecture solo: memory graph, RL logic, anti-hallucination layer, and cognitive pipeline. Mechanical engineering background with self-taught deep expertise in ML, PyTorch, embeddings, and graph-based memory systems.
Connect
Interested in defense AI, healthcare systems, or cognitive architecture? Let's talk about how MIG can integrate with your stack.
neel@houseofgalatine.com