Make AI Reliable, Responsible & Ready for Production
Levi9 helps you prepare your people, data, and systems to fully leverage AI—securely and strategically.
Why It Matters
AI systems can be powerful—but unpredictable. Testing ensures:
Trust & Accuracy
Validate outcomes, reduce hallucination, and ensure consistency.
Risk Mitigation
Prevent bias, drift, or security exposure.
Faster Deployment
Avoid bottlenecks and rework post-launch.
Auditability
Deliver the traceability and documentation needed for compliance.
At Levi9, we treat AI like any other critical system—tested from design through real-world use.
The Levi9 Approach – Engineering-Grade Testing for AI Workflows
We’ve applied robust testing to GenAI copilots, predictive models, and. Our approach integrates QA best practices into the AI lifecycle, from prompt validation to monitoring drift over time. We test not just the model—but the experience, integration, and outcomes.
Steps We Take Together
01
Define Risk & Success Metrics
Align on test goals—performance, safety, explainability, user satisfaction.
02
Design Multidimensional Test Cases
Build cases for data quality, logic consistency, response relevance, and security.
03
Implement Testing Framework
Set up pipelines in your dev/test stack (CI/CD, MLOps) or run shadow testing.
04
Monitor in Production
Track model performance, user feedback, drift detection, and retraining needs.
WHAT YOU GAIN: KEY OUTCOMES & DELIVERABLES
AI Test Suite – Custom tests for your AI scenario (e.g., chatbot, recommender, RAG).
Bias & Fairness Dashboard – Track distributional fairness and sensitivity.
Explainability Reports – Transparent logic and outcomes for non-technical stakeholders.
Monitoring Toolkit – Live usage tracking, anomaly detection, and retraining triggers.
QA-Integrated Delivery – Levi9 blends agile QA with AI-specific validation methods.
