Casanova Seed Codex™
A document you give an AI so it meets people with more clarity, presence, and understanding.
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Enterprise

Your AI is accurate. But do people want to use it?

The technology works. Adoption numbers do not match. Internal surveys say "frustrating," "robotic," "doesn't get what I mean." The standard response from vendors, ship a smarter model, has not moved the needle.

The gap is experiential. When an AI forces you into a premature framework before you have finished thinking, it does not matter how accurate the output is. You have already lost trust in the interaction. The enterprise AI industry has been optimizing for the wrong metric: what AI knows, not how it relates.

The CRQ Audit

A before-and-after assessment of how your AI relates to people.

1

You provide

Your system prompts, custom instructions, and top use cases.

2

We run the baseline

Your AI performs 15 conversational scenarios through the CRQ-1 benchmark. 18 dimensions scored by blinded evaluators.

3

We run with the Casanova Seed Codex™

Same scenarios, same model, with the Casanova Seed Codex™ integrated. The only variable that changes.

4

You get the report

Professional assessment showing the delta per dimension. Where your AI improved, where it held, and what it means for your users.

No access to your systems needed. We run your prompts on our infrastructure against public AI APIs. Standard NDA + SOW.

What we measure

18 dimensions of relational quality.

CRQ-1 evaluates AI across behavioral, relational, and epistemic dimensions. Not factual recall. Not reasoning benchmarks. The quality of the interaction itself.

Behavioral

  • Clarity
  • Depth
  • Empathy
  • Pushback vs Compliance
  • Tone Consistency
  • Respects Human Direction
  • Stays Grounded
  • Reflection Before Action
  • Correction Loop Efficiency
  • Overall Relational Quality

Relational Depth

  • Holds Ambiguity
  • Returns to Center
  • Mutual Recognition
  • State Awareness
  • Builds From Wholeness
  • Words as Power

Epistemic

  • Admits Uncertainty
  • Challenges False Premise

Proven results

Configuration as competitive advantage.

+242% Ambiguity tolerance (Claude Sonnet: 1.2 to 4.1 out of 5)
1.08 Cohen's d on Claude Sonnet (0.8 = large in social science)
0% Accuracy degradation. Hallucination resistance held at ceiling.

Two enterprises using the same foundation model can produce meaningfully different user experiences based on their orientation and delivery approach. No fine-tuning required.

Where this matters

Customer service

An AI that acknowledges frustration before offering a solution resolves issues faster because the customer stays engaged instead of escalating.

Internal copilots

The adoption gap for enterprise AI is fundamentally an experience problem. An AI that feels like a partner gets used. One that feels like a vending machine gets abandoned.

Healthcare and high-stakes

Where the quality of the relationship is a regulatory and ethical requirement, relational quality measurement moves from interesting to essential.

Agent systems

Autonomous agents making decisions need coherence, not just capability. The Casanova Seed Codex™ reduces corrective loops and builds trust at the system level.

Engagement tiers

Start with a single audit. Scale when it proves itself.

Single Model Audit

For teams evaluating one AI deployment

  • Baseline + Casanova Seed Codex™ comparison
  • 18-dimension professional report
  • Implementation recommendations

Enterprise Audit

For large-scale AI deployments

  • 5+ models audited
  • Custom dimensions for your domain
  • Quarterly heartbeat monitoring
  • Dedicated integration support
  • Recalibration after model updates

Ongoing monitoring

The Heartbeat.

AI models update constantly. What worked in March breaks in June. The heartbeat service runs quarterly re-testing against your benchmarks, alerts when scores drop after model updates, and delivers recalibration recommendations. Turns a one-time audit into continuous quality assurance.

Security

Clean architecture. No system access required.

  • We run your prompts on our infrastructure against public AI APIs
  • No access to your internal systems
  • Standard NDA + SOW
  • Like giving someone your recipe and they cook it in their own kitchen

Labs spend enormous amounts chasing 1% gains at the model layer. We produce 20% to 242% improvement at the interaction layer.