Solutions Built Around AI Quality
Three focused services designed to test, harden, and monitor your AI systems. Each works independently or as part of a comprehensive quality programme.
Back to HomeHow We Work
Every prismars.pro engagement follows a consistent methodology: we begin with a discovery phase to understand your AI systems, their deployment context, and your team's priorities. From there, we define clear objectives, build out the testing or monitoring infrastructure, execute the work collaboratively, and deliver comprehensive documentation alongside team training.
This process is adapted to the specific needs of each service — but the underlying commitment to structured, reproducible, and transparent work remains the same across all three offerings.
AI Quality Assurance Program
A comprehensive testing and validation program for AI systems covering functional correctness, robustness, edge case handling, and regression behaviour. We establish testing frameworks, create test case libraries, and implement continuous evaluation pipelines. Scope includes unit-level model tests, integration tests, and end-to-end scenario validation. Designed for organisations seeking systematic quality governance over their AI portfolio.
RM 7,100 · 6–10 weeks
- Functional correctness validation
- Regression test library creation
- Continuous evaluation pipeline setup
- Edge case identification and cataloguing
- Documentation and team training
Process
Adversarial Robustness Testing
Specialised testing to evaluate how your AI models perform under adversarial conditions — including input perturbations, distribution shifts, and deliberately crafted edge cases. We identify vulnerability patterns and quantify robustness boundaries. Results are documented with severity ratings and targeted hardening recommendations. Particularly relevant for safety-critical applications or systems exposed to untrusted input sources.
RM 4,800 · 3–5 weeks
- Input perturbation testing
- Distribution shift simulation
- Severity-rated vulnerability report
- Hardening recommendations
- Robustness boundary quantification
Process
AI Monitoring & Observability Setup
Design and implementation of monitoring systems that track AI model health in production — including prediction quality, data drift, feature stability, and operational metrics. Covers dashboard creation, alert configuration, logging standards, and incident response procedures. Enables your team to detect and respond to model degradation before it impacts business outcomes. Includes documentation and team training.
RM 3,600 · 4–6 weeks
- Custom dashboard creation
- Alert and escalation configuration
- Data drift detection setup
- Incident response runbook
- Team training and handoff
Process
Which Solution Fits Your Needs?
Use the comparison below to identify which service addresses your most pressing challenge — or combine them for comprehensive coverage.
| Feature | QA Program | Adversarial Testing | Monitoring Setup |
|---|---|---|---|
| Test Suite Development | |||
| Adversarial Attack Simulation | |||
| Production Dashboard | |||
| Drift Detection | |||
| Vulnerability Reporting | |||
| CI/CD Pipeline Integration | |||
| Team Training |
QA Program
Best for teams building new AI systems or refactoring existing models
Adversarial Testing
Best for safety-critical or externally exposed AI applications
Monitoring Setup
Best for production systems that need ongoing health tracking
Professional Standards Across All Solutions
Data Security
NDA-protected engagements with support for on-premise execution where required by your data governance policies.
Version Control
All test suites, configurations, and monitoring setups are version-controlled and reproducible for audit or re-evaluation.
Transparent Communication
Regular progress updates, shared workspaces, and open channels throughout the engagement lifecycle.
Scope-Based Pricing
Each price reflects a standard engagement scope. For larger or more complex AI portfolios, we provide tailored proposals after an initial assessment.
QA Program
6–10 weeks
per engagement
- Full test framework
- Test case library
- CI/CD integration
- Training & docs
Adversarial Testing
3–5 weeks
per engagement
- Perturbation testing
- Vulnerability report
- Hardening plan
- Team briefing
Monitoring Setup
4–6 weeks
per engagement
- Custom dashboards
- Alert configuration
- Drift detection
- Training & runbook
Not Sure Which Solution You Need?
Reach out and tell us about your AI systems. We will help you identify the right starting point — or design a combined programme that covers all your priorities.
Talk to Us