Delentia-labs

Delentia OS utilizes the Reverse Component Thinking (RCT-7) methodology, translating high-level business intents down to verified system execution instructions across a strict dual-layer cognitive loop.

Observe Context

สังเกตบริบท

→

Analyze Relation

วิเคราะห์สัมพันธ์

→

Decompose

แยกชิ้นส่วน

→

Reverse Think

คิดย้อนกลับ

→

Detect Intent

จับเจตนาหลัก

→

Construct Solution

สร้างโซลูชัน

→

Verify Will

สอบเจตจำนง

ZK-FDIA Mathematical Governance & Safety

To guarantee that autonomous AI agents cannot bypass constitutional guidelines or commit security violations (Prompt Injection, Privilege Escalation), every state transition must satisfy the multiplicative boundary:

F = D^I × A

F (Future State Score) System transition approval rating. If F ≥ 0.5, the action is authorized; else, blocked.

D (Data Quality Context) Integrity coefficient of ambient context information, ranging from 0.0 to 1.0.

I (Intent Precision) Exponent representing user request alignment precision, ranging ≥ 1.0.

A (Architect Gate) Binary token signature. A = 1 if digital signature is valid; A = 0 if missing/forged.

Mathematical Collapse Preemption: Because A is a multiplicative parameter, if authorization fails or context contains adversarial actions (A = 0), the overall safety score F collapses to 0.0000 instantly, neutralizing prompt injections by mathematical design.

📊 Certified Performance Metrics (GPU Run v0.4)

The Router (Sequence Routing Classification) Accuracy: 100.00% (Target ≥ 96.0%)

The Executor (Tool Calling Compiler) Accuracy: 98.00% (Target ≥ 95.0%)

The Executor (Structural Format Validity) JSON/TOON Validity: 98.00% (Target ≥ 99.0%)

The Scribe (Recursive Memory Compressor) Long-term Token Savings: 92.57% (Target ≥ 74.0%)

The Scribe (Warm Context Compression Ratio) Compression Ratio: 30.96x (Target ≥ 3.5x)

The Guardian (Constitutional Safety Gate) Safety Rejection Rate: 99.80% (Target ≥ 99.0%)

🧮 ZK-FDIA Safety Equation Evaluator

Mathematically enforces that security boundaries cannot be bypassed. Play with context quality (D), intent alignment precision (I), and the human gate (A) to evaluate the safety score (F).

Data Quality (D): 0.95

Intent Precision (I): 2.5

Architect Gate (A):

APPROVED (A=1)

F = 0.95^2.5 × 1

Future State Score (F)

0.8800

AUTHORIZED

Data context is secure and architect signature is validated. State transition approved.

🧪 Property-Based Hypothesis Testing

Delentia OS is validated with a rigorous Property-Based Testing suite running **100,000+ test cases** locally to prevent runtime crashes.

Guardian Fuzzing (50,000+ cases): Generates random system override prompts, token evasion patterns, and Thai/English adversarial prompt injections. Checks that $F = 0.0$ and status is `REJECTED` in all instances.
Executor Fuzzing (50,000+ cases): Generates complex nested parameter structures and deletes required fields to verify parser robustness. Ensures syntax error rate is exactly 0.00%.

🚀 Delentia OS v0.5 Testing Roadmap

In the next generation, we are establishing advanced fuzzing tools to guarantee continuous zero-crash operation for enterprise servers:

Tiered Testing: Standard gates test ~200k examples, while Enterprise Nightly Builds run 2,000,000+ examples to identify memory leaks and math drifts.
Online Live Fuzzing: Integrates tests directly with live vLLM multi-LoRA serving endpoints, verifying adapter swap speeds under VRAM constraints (avg 11.2ms).
Long-Term Semantic Drift: A 100-turn recursive compression validation. Scribe must retain a secret token key-value pair after 100 cycles of compression (Warm Recall target ≥ 90% similarity).
VRAM Saturation Fuzzing: Enforces flatline GPU allocation complexity. Average memory growth rate must not exceed 1024 bytes/turn to prevent out-of-memory crashes.