Why This Works: The Closed Loop
Training creates consistency. Evaluation provides evidence. Together they create a closed loop that builds trust and enables scale.
See Our ApproachA Proven Approach to AI Adoption
Our methodology works because it addresses the root causes of AI stalling: lack of consistency and lack of evidence. By combining training-led consulting with evaluation tools, we create a closed loop that builds trust and enables confident scale.
Why It Works
- • Addresses root causes, not symptoms
- • Creates a closed loop of continuous improvement
- • Provides both skills and evidence
- • Enables confident scale through trust
The Closed Loop
1. Train Teams
Build skills and consistency through hands-on training
2. Evaluate Outputs
Measure quality and capability against standards
3. Pick Right Model
Make data-driven decisions based on evidence
4. Integrate Solution
Deploy proven solutions into production
5. Repeat with Refresh
Continuous improvement with quarterly updates
Each cycle builds on the last, creating stronger trust and broader adoption.
Training → Consistency
When teams are trained, everyone uses AI the same way, best practices are shared and followed, risk is understood and managed, and confidence grows through competence.
Result: Consistent, predictable AI usage across your organization.
Evaluation → Evidence
When outputs are evaluated, quality is measured and verified, capabilities are proven against real tasks, failures are identified and mitigated, and decisions are backed by data.
Result: Evidence-based confidence in AI capabilities.
Together → Trust
Training enables evaluation by creating skilled practitioners who know what to evaluate. Evaluation guides training by revealing capability gaps and quality issues.
Together they build trust: consistent usage reduces variance, evidence reduces uncertainty, and the combination creates trust that enables confident scale.
The combination is more powerful than either alone.
Measurable Results
Fewer Dead-End Pilots
Evaluation identifies winners before commitment. Training ensures proper usage. Evidence prevents poor decisions. Trust enables confident deployment.
Result: 60-80% reduction in failed pilots
Faster Time-to-Value
Training accelerates adoption. Evaluation speeds decision-making. Integration happens faster with confidence. Closed loop enables continuous improvement.
Result: 2-3x faster time-to-production
Defensible Decisions
Model selection backed by benchmarks. Investment decisions supported by ROI. Quality claims verified by evaluation. Strategic planning based on capability data.
Broad Daily Adoption
Consistent usage patterns. Embedded routines in workflows. Self-service capabilities. Executive confidence enabling sponsorship.
Ready to Build Your Trust Layer?
See how training and evaluation work together to create the closed loop that builds trust and enables confident AI adoption.