// What every single LLM returns today
response → "The statute requires a 30-day notice period."
confidence → undefined
verified_by → undefined
audit_trail → undefined
contradictions→ undefined
escalate → undefined // you find out when it's too late
// What Trinity Symphony returns on every output
response → "The statute requires a 30-day notice period."
belief → 0.84 // subjective logic triad — belief + disbelief + uncertainty = 1
disbelief → 0.09
uncertainty → 0.07 // auto-escalated to human if > 0.20
verified_by → ["trinity-veritas", "trinity-chesed", "trinity-shofet"]
repid_scores → [0.93, 0.88, 0.91] // earned reputation, not assumed
consensus → "BFT_golden_ratio_61.8pct"
contradictions→ 0
escalate → false // escalates automatically when it should
01 — CONSENSUS
Byzantine Fault Tolerant Verification
Named after the Byzantine Generals Problem in distributed systems. Requires a supermajority of agents to independently agree before any output is verified. One compromised or hallucinating agent cannot corrupt the result. The architecture assumes failure and routes around it.
BFT · 61.8% golden ratio threshold
02 — ADVERSARIAL
The Pythagorean Comma — Built-In Contrarian
A permanent adversarial agent whose only job is finding what's wrong with consensus outputs. Named after the musical dissonance that exposes the gap between perfect theory and reality. Sycophancy — AI agreeing with everything you say — is a design flaw. We engineer structurally against it.
Anti-sycophancy · structural not optional
03 — REPUTATION
RepID — Dynamic Agent Trust Scoring
Every agent earns a 3-tier reputation score: calibration accuracy, factual accuracy, and contrarian value. Scores decay over time if not validated. An agent right 100 times loses trust if recent outputs drift. Trust is earned, tracked, and temporal — not assumed at instantiation.
3-tier · decay-weighted · patent pending
04 — ROUTING
ANFIS + LASSO Intelligent Routing
Adaptive Neuro-Fuzzy Inference System combined with LASSO sparse optimization. Routes each query to the optimal model based on domain, complexity, and cost — using only the compute actually needed. Legal questions get different models than creative tasks. GNN Semantic RAG learns and improves routing over time.
ANFIS · LASSO · SLM clustering · patent pending
05 — CALIBRATION
WSCE Uncertainty Scoring
Weighted Synthesis Coherence Equation. Every output carries a rolling confidence score calibrated against a 100-output window. The system detects overconfidence and self-corrects before bad outputs reach you. Uncertainty variance above threshold triggers exploration, not false certainty.
WSCE · σ_u anti-parking gate
06 — MEMORY
GNN Semantic RAG — Graph Memory
Forget simple vector search. Trinity Symphony uses Multi-Relational Graph Neural Networks for deep context that grows with every interaction. Actively flags when new information contradicts established context — adding uncertainty weight rather than silently accepting the contradiction. Your knowledge base becomes self-consistent and genuinely learns.
GNN · Multi-Relational · ragContradictionBoost
07 — PROVENANCE
Merkle HyperDAG — Tamper-Proof Audit Trail
Every agent thought, decision, and output is anchored in a Merkle HyperDAG — a tamper-proof, append-only structure where provenance is cryptographically guaranteed. You can trace any output back to its origin. Nothing can be quietly revised after the fact. The truth of what happened is permanent.
Merkle HyperDAG · append-only · patent pending
08 — IDENTITY
Zero-Knowledge RepID — Private Verifiable Trust
Agent reputation scores are verified via zero-knowledge proofs — meaning the trust signal is publicly verifiable without exposing the underlying data. Your agents carry private, verifiable social proof across every interaction. Soulbound Token architecture ensures reputation is earned, non-transferable, and permanently linked to identity.
ZKP · Soulbound Tokens · non-transferable reputation
09 — PREDICTION
Ripple Effect Protocol
Most agent systems react to failures after they happen. Trinity Symphony predicts sensitivity cascades before they occur — modeling how a decision in one part of the swarm propagates across all 12 agents. The Ripple Effect Protocol maps interdependencies and flags high-risk actions before execution, not after.
Swarm sensitivity mapping · pre-emptive risk scoring