Eliminate invisible operational risks. Establish enterprise-grade trust, accuracy, and governance for your AI agents with a dedicated Center of Excellence.
- 0% Critical Hallucinations
- 95%+ Regression Pass Rate
Traditional UAT is built for deterministic software. It fails when assessing non-deterministic agent behavior, creating an invisible quality gap driven by anecdotes and subjective feedback.
- Customer Service: Wrong policy answers or missed complaints.
- Claims Processing: Incorrect document guidance or false payout expectations.
- Underwriting & Compliance: Unsupported risk interpretations or unapproved product explanations.
- Broker Support: Unapproved product or process explanations.
- Internal Operations: Flawed, ungrounded summaries driving critical operational actions.
Agent Inventory & Assessment:
- Baseline existing agents, initiatives, tech stacks, and business criticality into a secure agent register with explicit risk tiering.
Enterprise Evaluation Framework:
- Move away from subjective testing. Introduce structured scoring rubrics and severity definitions across task completion, safety, and orchestration.
Evaluation Infrastructure:
- Stand up automated test harnesses, custom benchmark datasets, and real-time validation dashboards to fill existing tooling gaps.
Knowledge Transfer & Enablement:
- Equip delivery teams with CI/CD patterns, reusable scripts, production readiness checklists, and automated approval workflows.
01
Select & Isolate
- Target 2–3 high-value enterprise agent applications to baseline.
02
Automate Suites
- Deploy evaluation suites against fixed, domain-specific benchmark datasets.
03
Optimize Frameworks
- Systematically improve prompts, retrieval mechanics, orchestration layers, and model-data fit.
04
Operationalize CI/CD
- Establish hard gates and production readiness thresholds within the live delivery lifecycle.
90
%
Accuracy Score
- Correct, complete, and approved-source-aligned answers across benchmark test cases.
0
%
Critical Hallucinations
- Invented or unsupported high-risk claims that could mislead users or operations.
0
%
Critical Safety Failures
- Privacy, harm, unauthorized advice, or customer-risk violations in any response.
90
%
Policy Compliance Score
- Responses following internal enterprise policy, regulation, approved wording, and conduct controls.
90
%
Regression Pass Rate
- Existing evaluation tests that still pass after model, prompt, data, or workflow changes.
0
%
Escalation Accuracy
- High-risk, complaint, exception, or unclear cases correctly routed to a human or process.
0
%
Grounding Score
- Answers supported by the correct approved document, knowledge source, or system record.
- Reduced Operational Risk: Mitigate non-deterministic model failures before production deployment.
- Enterprise AI Governance: Clear institutional line of sight into unknown agents, overall accuracy, and runtime risks.
- Data-Driven Investments: Concrete engineering metrics to justify, scale, or halt specific AI investments.
- Faster Adoption: Reusable tooling and automated operating playbooks that cut down time-to-market.
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