Layer 3 · Company AI Cognition

Most companies know employees are using AI. Almost none know how AI is changing their thinking.

Mentiscore audits company AI interactions to reveal where AI improves decisions, where it creates false confidence, and which models actually produce better work.

Company-level signal Model impact scoring Decision-risk detection
This is not about AI usage.

It is about whether AI is making your company smarter — or just faster and more confident.

The real enterprise problem

Companies don’t need another AI tool. They need visibility into how AI is changing their thinking.

Same company. Same people. Different AI model. Different decision behavior. That is the layer Mentiscore measures.

What leadership gets

From messy AI usage to company intelligence.

Mentiscore turns anonymized AI interactions into a structured audit of behavior, risk, and model impact.

01

Decision quality

Do teams use AI to improve decisions, or to justify decisions already made?

03

Model impact

Which AI model improves clarity, reasoning depth, decision speed, and execution quality?

Demo

Run a sample company cognition scan.

This demo shows how a company-level AI audit can become a leadership report.

Company scan input

Paste company AI interactions.

In production, this can work with anonymized exports or approved workspace integrations.

Live analysis pipeline

From prompts to decision intelligence.

The report is not a vibe check. It is a structured read of the interaction patterns that shape real company decisions.

1
Extract model usage patterns ChatGPT, Claude, Gemini, Grok, internal tools
ready
2
Score cognition signals framing, validation, iteration, closure
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3
Detect invisible decision risk false confidence, shallow validation, analysis loops
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4
Generate company AI cognition report benchmark, model impact, leadership recommendations
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Strategic AI Operator

Your company uses AI to create clarity and structure, but validation behavior is not yet consistent enough for high-stakes decisions.

76 AI cognition
Uncomfortable truth

Your teams are getting clearer answers from AI, but they are not consistently challenging those answers before turning them into decisions.

Model impact intelligence

Your AI model choice quietly changes company behavior.

Mentiscore compares models by their effect on human work: reasoning depth, clarity, speed, validation, and decision quality.

Claude effect

Better reasoning depth. Slower closure.

Strong for strategic exploration, scenario planning, legal reasoning, and complex tradeoffs. Risk: analysis can become too comfortable.

+6% deeper reasoning chains in complex workflows
Gemini effect

Faster summarization. Lighter challenge.

Strong for research compression, information scans, and rapid comparison. Risk: teams may move faster without deeper validation.

+3% faster movement from information to recommendation
State-of-the-art analysis

We measure the behavior around the AI, not just the AI output.

Mentiscore reads how work actually happens: how teams frame, prompt, challenge, iterate, converge, and convert AI output into decisions.

Signal 01 Framing quality

Do people define the problem before asking AI for the answer?

Signal 02 Iteration depth

Do they refine thinking or keep restarting with shallow prompts?

Signal 03 Validation behavior

Do they challenge AI output before using it in real decisions?

Signal 04 Decision closure

Does AI help them decide, or does it create more analysis loops?

The enterprise wedge

“We show you which AI model is improving your company’s thinking — and which one is creating risk.”

This turns AI adoption from a tool-choice conversation into a measurable intelligence layer for leadership.

Run the demo scan