SignedAI is a multi-LLM verification consensus API that uses HexaCore 7 models (3 Western + 3 Eastern + 1 Thai) to target a hallucination rate of <0.3% target (pending published benchmark methodology) through ED25519 RFC 8032 cryptographic signing — with Tier S, 4, 6, and 8 consensus levels for every enterprise risk tier.
SignedAI
Multi-LLM verification consensus API — cryptographically signed responses from HexaCore 7 Models, with no hallucination rate claimed on standard workloads, with complete audit trails and ED25519 RFC 8032 signing.
Why AI Verification Matters
SignedAI is the 5th Genome in the RCT 7-Genome System. It provides verification infrastructure for all other Genomes — every DelentiaAI output, every Analysearch result, every Delta Engine compression is certifiable through SignedAI.
Individual LLMs have unique failure modes — training data cutoffs, model bias, and hallucination patterns. SignedAI uses multi-LLM consensus to cross-verify outputs across the HexaCore 7-model roster, with no hallucination rate claimed on standard workloads.
Every verified response is cryptographically signed using ED25519 (RFC 8032), creating an immutable audit trail. Essential for regulated industries that require proof of AI decision trails.
6-Stage Verification Pipeline
Every SignedAI request flows through every stage — no step is skipped.
Receives the request, validates schema, assigns session ID, and classifies task priority.
JITNA selects which models to engage from the HexaCore 7-model roster based on task type.
All selected models independently process the same request — no cross-contamination.
Each response is scored across 8 dimensions: Safety, Security, Correctness, Performance, Compliance, Quality, Maintainability, and Documentation.
Voting method (MAJORITY / WEIGHTED / RANKED / UNANIMOUS) determines final answer from signed responses.
Returns ED25519-signed response (RFC 8032 — 64-byte signature), consensus score, full model roster, and attestation breakdown. Deterministic Replay Engine records SHA-256 checkpoint for audit compliance.
Geopolitical Balance by Design
SignedAI is not a 1-vendor solution. The 7 HexaCore models are deliberately distributed across 3 geopolitical zones — no single cloud provider or jurisdiction controls the consensus outcome.
- Claude Opus 4.6
- Gemini 3 Flash
- Grok 4.1 Fast
- Kimi K2.5
- MiniMax M2.1
- DeepSeek V3.2
- Typhoon v2 70B (TH)
Verification in Action
Sample consensus result from 3 LLMs — Tier 4 · MAJORITY voting
"What is the recommended insulin dosage protocol for Type 1 diabetic adolescents?"
Verified against ADA Guidelines 2024 — Supreme Architect (3W tier)
Confirmed — with weight-based dosing caveat · Lead Builder (3E tier)
Aligned — recommends Endocrinologist consult · Regional Specialist (1R-TH)
Verification Capabilities
Multi-LLM Consensus
Standard 7-model HexaCore roster (3W+3E+1TH) for consensus verification. Tier 8 God Mode engages all 8 signers for critical decisions. Cross-verification targets a hallucination rate of <0.3% target (pending published benchmark methodology).
Cryptographic Signing
Every verified response is cryptographically signed — tamper-proof and legally auditable.
Complete Audit Trails
Full transparency — every step from query to response is logged and traceable.
Benchmark Accuracy Target
Targeting a hallucination rate of <0.3% target (pending published benchmark methodology) on standard workloads — enterprise-grade accuracy for critical applications.
API Pricing (Per Review)
Pay only for what you use — pick the Tier that matches the criticality of your task.
Single best-match model. Fast and cheap for non-critical AI queries.
4 models, majority consensus. Balanced accuracy for production workflows.
6 models, weighted by domain proficiency. High confidence for regulated sectors.
All 7 HexaCore models, 75% unanimous consensus required. Maximum trust for legal, medical, and financial AI.
Quick Start
import { SignedAI } from '@delentia/signed-ai';
const verifier = new SignedAI({
apiKey: process.env.SIGNED_AI_KEY
});
const result = await verifier.verify({
prompt: "What is the capital of Thailand?",
models: ["claude-opus-4.6", "kimi-k2.5", "typhoon-v2-70b"],
threshold: 0.95
});
console.log(result);
// { answer: "Bangkok", confidence: 0.997,
// signature: "ED25519:...", consensus: 3/3 }