MDIL REMAP — Zero-Trust Reasoning for Agentic AI. Move your agent's decisions onto a deterministic, auditable plane: no tokens, no GPU, every decision declared.
REMAP wraps the agent you already have and moves its decisions onto a deterministic plane — no tokens, no GPU, every decision audited. The model keeps writing. It stops deciding.
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Reasoning separated from generation.
The decision is made before the LLM is invoked. Routing, guards, privacy, are-we-done — deterministic computation, no model in the loop. A model is called only for the part that genuinely needs writing.
None, on the common path. The decisions run on a single CPU core, in under a gigabyte — tens of instances side by side, near-real-time. It runs on the hardware you already own.
Decisions are made by declared, deterministic detector ensembles — MMTs — not trained weights. Every result lands in a hash-linked, tamper-evident audit chain built for regulator review.
REMAP wraps the exact points where an agent goes off the rails and moves those decisions onto the deterministic plane. Your framework, tools, prompts and code stay.
Zero-Trust reasoning infrastructure for agentic AI.
REMAP is the first product built on MDIL — a deterministic reasoning layer any agent stack can run on. Zero-trust operation is its flagship profile.
No model in the decision loop — authored logic that can be read, replayed and verified against what it declares.
What did it decide. Why. Show me. Hash-linked and tamper-evident — the three regulator questions, made boring.
Sensitive data is pseudonymized before it reaches any model — zero entity bytes cross the line.
Cloud, on-premise, or fully air-gapped — identical behavior. Sovereignty as the deployment diagram, not a slogan.
Ask the thing itself.
Ask Airut anything about REMAP or MDIL — what it does, how the audit chain and Symbol Security work, or how to claim a place.
A decision plane with nothing to take on faith.
Zero trust's tenets survive, but the principal changed — the reasoning path between request and action is the lane no perimeter control governs today.
Detection equals declaration: the model proposes, declared policy disposes, and Symbol Security pseudonymizes before the model sees anything.
Enforcement from parse time to every run: gates at each rung, a declared fail direction, every decision in a replayable audit chain.
SP 800-207, MITRE ATLAS, both OWASP Top-10 lists, NIST AI RMF, the EU AI Act — mapped tier by tier, with the limitations stated plainly.
Where MDIL sits in your zero-trust architecture, how to pilot it (verify before you trust), what to audit, and determinism as contestability.
The full paper opens right here the moment you sign up — hosted, readable in the browser — and the same reading link lands in your inbox. No PDF, no separate request.
The full concept paper is open on your link — hosted, readable in the browser. Start with the executive summary, or jump to any chapter from the cards above.