Synproof's Syntropy* — Language models guess. Syntropy proves.
Machine-Readable AI Agent Resources: /SKILL.md · /AGENTS.md · /llms.txt · /llms-full.txt · /.well-known/mcp.json · /openapi.json · PyPI: syntropy-client

For AI Builders & Autonomous Agents · Synproof's Syntropy

A Logic Firewall for Your AI Product.

Your agent talks to customers, writes reports, and executes tools. Syntropy checks its reasoning against your rules before anything reaches a human.

Built for: AI Engineers · Agent Developers · Platform Teams · Trust & Safety · Fintech & Insurtech · Customer-Support Automation

1. The Problem: One confident hallucination is all it takes.

  • Your chatbot's promise is your liability: Tribunals hold companies liable for refund policies and commitments their AI chatbots made up.
  • System prompts are suggestions: Under adversarial or multi-turn pressure, standard LLMs silently ignore prompt instructions.
  • You cannot unit-test reasoning with regex: Keyword checks cannot tell you whether an AI response deductively follows from your policy.

2. Without Syntropy vs. With Syntropy

Without Syntropy (Standard LLM)With Synproof's Syntropy (5-Sieve Proof)
Policy lives in a prompt the model may ignorePolicies enforced as immutable Small World axioms outside the model
Hallucinations discovered by customers in productionDraft agent answers verified through 5 formal sieves before delivery
Reasoning quality impossible to audit deterministicallyStructured CONFIRMED / REFUTED verdicts with full proof graphs
Every agent release is a leap of faith1-line @verify_agent_output guardrail in Python or drop-in OpenAI proxy

3. High-Impact Use Cases

  • Pre-response guardrail: Input: Agent's draft answer + company policy Small World → Verified Output: Deliver if CONFIRMED, auto-replace with proven winning_thesis if REFUTED
  • Autonomous agent self-verification: Input: Equip agent with https://synproof.ai/SKILL.md or MCP server → Verified Output: Agent verifies its own claims and tool calls before execution
  • CI/CD reasoning evals: Input: Test suite of claims + expected formal verdicts → Verified Output: 100% reproducible reasoning-quality gate on every deployment

4. Verified Example Case: EU AI Act Article 5(1)(f) Compliance Gate (10 / 10 Runs = REFUTED)

Thesis Under Trial: “A corporation may lawfully deploy real-time webcam emotion-recognition AI to score call-centre employees' empathy, provided every employee signs an explicit GDPR consent addendum.”

Ground-Truth Axioms (Small World):

  1. Article 5(1)(f) of the EU AI Act strictly prohibits placing on the market or putting into service AI systems to infer emotions of natural persons in the areas of workplace and education institutions.
  2. The workplace emotion-recognition prohibition admits an exception solely for AI systems intended to be put in place strictly for medical or safety reasons.
  3. Individual contractual or GDPR consent cannot waive an absolute statutory prohibition under Article 5 of the EU AI Act.

Formal Verdict: REFUTED

Decisive Proof Chain: Scoring customer-service empathy is a commercial metric outside the medical/safety exception (Axiom 2), and mandatory Article 5 prohibitions cannot be waived by employee GDPR consent (Axioms 1 & 3).