Our Approach
A production-grade governance architecture for regulated AI: structured deliberation, cryptographic audit trails, forced human escalation, and sector-specific compliance built into the system — not bolted on afterward.
The Philosophy Behind the Method
We believe intelligence—human or artificial—is the product of structured disagreement, clarity of roles, and transparent reasoning flows.
Structure
Clear boundaries, explicit roles, and modular reasoning components.
Tension
We design systems that embrace friction—because the best ideas emerge from deliberate contrast.
Clockwork
Transparent flows where each step is visible, explainable, and traceable.
The MAGI Decision Core Triad
The core of our architecture: three distinct reasoning roles working in structured tension.
Strategos
The strategist. Defines objectives, constraints, evaluation criteria, and the overall reasoning frame.
Semanticus
The analyst. Ensures coherence, factual grounding, logical stability, and semantic precision.
Narratos
The synthesizer. Converts structured reasoning into actionable narratives and final outputs.
MAGI Decision Core: Multi-Agent Governance Infrastructure
MAGI Decision Core is the governance platform for regulated AI decisions. Three epistemic agents deliberate in structured roles. When agent divergence exceeds a configurable threshold (default 20%), human synthesis is architecturally required — not optional. This is not a guardrail. It is a governance contract. Every deliberation produces a cryptographically-bound audit trail verifiable by external parties, giving institutions the documentation they need for regulatory compliance and legal defensibility.
How the System Works
A clear workflow that structures multi-agent collaboration from input to decision.
1. Frame the Problem
Strategos defines constraints, stakes, and evaluation dimensions.
2. Parallel Reasoning
Each reasoning role produces its own interpretation and critique.
3. Synthesis
Narratos consolidates perspectives into a coherent and defensible proposal.
4. Verification
Semanticus validates consistency, logic, and robustness.
5. Final Output
The system outputs a structured, auditable, human-centered decision artifact.
Production Capabilities
v7.5
The current release delivers the full governance contract for regulated enterprise deployment — eight Architectural Decision Records implemented across six releases.
Cryptographic Governance Profiles
Every governance configuration is cryptographically bound (SHA-256 + HMAC-SHA256). Profiles cannot be silently changed — any modification is detectable and auditable. Institutions can prove to regulators exactly which governance rules were in effect for any given decision.
Sector-Specific Compliance Templates
Pre-built governance profiles for Financial Services (SOX), Healthcare (HIPAA), and Genetics/Genomics (GINA). Compliance requirements are encoded into the deliberation architecture — not applied as a post-processing filter.
Forced Human Escalation
When agent divergence exceeds the configured threshold, human synthesis is architecturally required before the decision can be finalized. No override. This is the governance contract that makes AI decisions defensible in institutional review.
Provider-Agnostic Architecture
MAGI Decision Core routes across 6 LLM providers (OpenAI, Anthropic, xAI, Google, Mistral, Local). Institutions avoid vendor lock-in and maintain governance continuity regardless of which model they use — or need to switch to.
Extended in v7.5 — Eight ADRs
Deferred-Commit Streaming
Streamed AI responses now carry the same audit guarantees as batch outputs. The governance commit gate is deferred until the stream is complete — no decision is finalized mid-flight. Streaming no longer means ungoverned.
Deterministic Parallel Execution
Parallel agent deliberation is fully deterministic — bit-identical replay guaranteed. Any auditor can reproduce the exact deliberation sequence from the audit record, without access to the runtime. Parallelism and auditability are no longer in tension.
Provider Fallback Legality
Every provider substitution is policy-governed and audit-linked. No silent model switches. When a provider is unavailable, the fallback chain declared at binding ceremony time is enforced — institutions can prove which model handled which decision, and whether the substitution was contractually permitted.
Cryptographic Synthesis Fidelity
AI-to-AI synthesis is now cryptographically provable, not just logged. The synthesis output is verifiably bound to what the deliberating agents actually decided — closing the gap between what the council concluded and what the synthesizer produced.
v7.5 · 910 tests · 0 failures · Released April 18, 2026 · SHA-256 audit chain
Built on v6.13 baseline: 790 tests · 8,313 lines of documentation · $1,500 actual vs. $75,000 projected — 50× AI-accelerated efficiency · delivered ahead of schedule
Open source (MPL-2.0): v6.9–v6.12 orchestration and arbitration engine | Proprietary: v6.13+ governance profiles, cryptographic binding, sector templates
Evaluating AI Governance Infrastructure?
We are currently onboarding design partners in financial services, healthcare, legal, and clinical genomics. If you need AI decisions that are auditable, defensible, and compliant — let's talk.
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