Customer Intelligence Protocol FAQs

Question 1

What is the Customer Intelligence Protocol (MCP)?

Accepted Answer

The Customer Intelligence Protocol (MCP) is a software server that uses a deterministic 4-layer scoring kernel to detect hidden risks ('friction') and optimal opportunities ('emergence') across any domain. It provides structure for AI reasoning, especially when integrated with LLMs.

Question 2

What role do LLMs play when used with Customer Intelligence Protocol?

Accepted Answer

LLMs translate real-world situations into the numerical layer inputs for the MCP kernel. Once MCP processes these inputs and returns a structured, deterministic score, the LLM then interprets what those numbers mean in context, providing actionable insights and explanations.

Question 3

What kind of output does MCP provide?

Accepted Answer

MCP provides a stable output envelope including an M-score (signal intensity), detection alerts/windows (risk or opportunity), layer attribution (which input drove the score), layer visibility (dominant hierarchical level), and layer coupling (coherence or tension between layers), all auditable.

Question 4

How does MCP prevent AI hallucinations and provide trustworthy outputs?

Accepted Answer

MCP provides bounded, auditable, and deterministic signals to LLMs, ensuring consistent and honest numerical scores. Its immutable core formula and built-in governance bounds mean every output is explainable, every override logged, and confidence is based on verifiable math, not 'vibes'.

Question 5

Can Customer Intelligence Protocol be adapted to different industries or specific problems?

Accepted Answer

Yes, MCP is highly configurable. It supports domain-specific profiles where you define layers, weights, and thresholds tailored to your context. The kernel itself is content-agnostic, making it suitable for analyzing everything from customer churn to geopolitical situations.

Customer Intelligence Protocol

Customer Intelligence Protocol

主要功能

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主要功能

使用案例