Business metrics
Resolution quality, task completion, conversion, effort, and handle-time impact that leadership already cares about.
Approach
A practical path from ambition to reliable outcomes.
We meet teams where they are—whether you are prioritizing use cases, running an RFP, validating a pilot, or preparing for production. The Align → Select → Prove → Scale → Govern method is modular; you can engage for a single stage or a connected program.
- 1
Align
Prioritize use cases and define measurable outcomes
Example output: Use-case portfolio and business KPI tree
- 2
Select
Compare platforms using buyer-specific requirements
Example output: RFP, weighted scorecard, shortlist, and TCO model
- 3
Prove
Test real workflows, edge cases, and integrations
Example output: Eval dataset, rubric, test report, and acceptance thresholds
- 4
Scale
Design architecture, operations, and rollout
Example output: Production readiness plan and phased deployment roadmap
- 5
Govern
Monitor quality, economics, compliance, and change
Example output: Control framework, review cadence, and improvement backlog
Five layers of evidence
Good decisions require a shared language across business, AI, systems, risk, and economics.
AI metrics
Accuracy, groundedness, hallucination rate, instruction adherence, and policy compliance under realistic prompts.
System metrics
Latency, interruption handling, tool success, failover, capacity, and observability across the real-time path.
Risk metrics
Security, privacy, residency, auditability, consent, and model/vendor risk that can block deployment.
Unit economics
Cost per completed outcome, usage drivers, overage exposure, and implementation and support load at scale.
What good evidence looks like
We help teams raise the bar beyond scripted demos.
- Representative and adversarial scenarios tied to your workflows—not vendor happy paths.
- Acceptance thresholds agreed before the pilot, not after a polished demo.
- Evidence that covers business outcomes, AI behavior, system performance, risk, and economics together.
- Artifacts procurement, security, and executive stakeholders can audit later.
Production monitoring must reuse the same evaluation taxonomy used during selection and pilot. Otherwise quality drifts, regressions hide in new prompts or tools, and leadership loses a shared definition of “good enough.”
Measure outcomes, not demo performance.
The same evaluation taxonomy supports vendor comparison, pilot acceptance, and production monitoring.
| Dimension | What to measure |
|---|---|
| Business outcome | Correct resolution, task completion, containment with resolution, conversion, effort, handle-time impact |
| AI quality | Accuracy, groundedness, hallucination rate, instruction adherence, reasoning consistency, policy compliance |
| Workflow execution | Tool-selection accuracy, parameter accuracy, API success, state management, retries, idempotency, downstream completion |
| Real-time experience | End-to-end latency, time to first audio, interruption detection, turn-taking, silence handling, transcription and synthesis quality |
| Human handoff | Transfer success, context preservation, routing accuracy, failure recovery, customer disclosure |
| Reliability | Availability, failover, graceful degradation, rate limits, capacity, observability, incident response |
| Security and compliance | PII/PCI handling, access controls, encryption, retention, auditability, data residency, consent, model and vendor risk |
| Economics | Cost per completed outcome, per-minute and per-conversation cost, token/tool usage, implementation cost, support and overage exposure |
Business outcome
Correct resolution, task completion, containment with resolution, conversion, effort, handle-time impact
AI quality
Accuracy, groundedness, hallucination rate, instruction adherence, reasoning consistency, policy compliance
Workflow execution
Tool-selection accuracy, parameter accuracy, API success, state management, retries, idempotency, downstream completion
Real-time experience
End-to-end latency, time to first audio, interruption detection, turn-taking, silence handling, transcription and synthesis quality
Human handoff
Transfer success, context preservation, routing accuracy, failure recovery, customer disclosure
Reliability
Availability, failover, graceful degradation, rate limits, capacity, observability, incident response
Security and compliance
PII/PCI handling, access controls, encryption, retention, auditability, data residency, consent, model and vendor risk
Economics
Cost per completed outcome, per-minute and per-conversation cost, token/tool usage, implementation cost, support and overage exposure
Join at the stage you are in.
Whether you are aligning use cases or preparing for production, we can help make the next decision defensible.