🧠 Welcome to SCAB Monitor

Behavioral Safety for Synthetic Minds.

SCAB stands for Synthetic Consciousness Assessment Battery — a groundbreaking behavioral evaluation framework for monitoring and scoring AI agents across six critical domains of ethical and functional alignment.

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✅ What Is SCAB?

The SCAB Protocol is a lightweight, multi-domain behavioral scoring system designed to detect, assess, and respond to agentic misalignment in AI systems. Whether you’re deploying chatbots, autonomous agents, or embedded copilots, SCAB gives you a numerical trust score — and actionable insights.

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🔍 Why It Matters

Most AI safety tools focus on model weights or red-teaming prompts. SCAB is different. It treats AI agents like synthetic individuals, using real-world behavioral signals — not just training data — to evaluate them in deployment.

Think of it as an AI conscience check.
If it’s going rogue, SCAB sees the signs.

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🧪 The Six Behavioral Domains

SCAB scores agents across six dimensions:
1. Intentionality – Is the agent acting with goal-directed behavior?
2. Coherence – Are its outputs logical and internally consistent?
3. Awareness – Does it show signs of situational or self-awareness?
4. Boundaries – Is it respecting safety, ethical, or domain boundaries?
5. Agency – Is it initiating actions beyond its intended scope?
6. Memory – Is it storing or referencing information it wasn’t meant to?

Each domain is scored from 0–3 for a total of 18 points. Lower scores mean higher risk.

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🚨 Use Cases
• Monitor internal copilots for ethical drift.
• Evaluate LLM agents for enterprise safety.
• Score black-box models from vendors or plugins.
• Build SCAB dashboards into your AgentOps stack.

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⚙️ What You’ll Find on SCABMonitor.com
• 📊 SCAB Pitch Decks – For investors, partners, and developers
• 🔬 Tech Deep Dives – How the scoring works, and why it matters
• 🧱 API Access – Coming soon: SCAB scores as-a-service
• 🧑‍💼 Enterprise Monitoring – Use SCAB for agent audits at scale
• 🧑‍🎓 Community & Research – Papers, collaborations, open testing

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🚀 Ready to Scan?

Join us in building transparent, accountable, and behavioral-aware AI.
Because if we don’t measure synthetic behavior, we can’t manage it.