Testing for systems that don't have a single right answer.
LLM outputs, agent behavior, RAG accuracy, prompt regression – Nexaq has built the validation primitives for AI systems that traditional testing tools were never designed to handle.
The Problem
Why This Matters Now
You can’t unit-test a language model. You can’t assert an agent. When your system’s output is probabilistic and context-dependent, ‘pass or fail’ isn’t a useful construct. Yet most teams ship AI features with no systematic quality validation at all – relying on vibes, manual spot-checks, and customer complaints to surface issues. Nexaq changes that.
What We Deliver
Purpose-Built Assurance for AI Systems
- Prompt engineering validation and output quality assessment
- Prompt Regression Testing: validate that model updates don't degrade your application's behavior
- Context consistency and response reliability validation
- Agent behaviour and decision-making validation
- AI model evaluation, benchmarking, and functional testing
- Safety, governance, and compliance validation for AI deployments
How It Works
Our Approach
Baseline Establishment
We characterize your AI system’s expected behavior across a curated test set – establishing baseline performance before any changes are made.
Evaluation Framework Design
We design custom evaluation rubrics and automated scoring pipelines tailored to your system’s specific quality dimensions.
Regression Integration
Evaluation runs are integrated into your CI/CD pipeline – every deployment triggers AI validation automatically before it reaches production.
Continuous Monitoring
Ongoing production monitoring detects quality drift, model degradation, and unexpected behavioral shifts over time.
Best for
This Solution Is Right For You If...
- LLM-powered applications (chatbots, copilots, AI search, recommendations)
- AI copilots and assistants
- Autonomous and agentic systems
- AI-driven enterprise workflows
Ready to Get Started?
Get a free AI validation assessment.
We’ll review one of your AI features, identify the top quality risks, and show you what systematic AI validation looks like for your specific stack. 30 minutes, no commitment.
