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AI Testing & Agent Evaluation

As AI systems become more autonomous and context-aware, evaluating their reliability, safety, and real-world performance is critical. At WalkingText, we provide a comprehensive AI Testing and Agent Evaluation framework that measures how AI agents behave, reason, and respond across diverse scenarios.
Our evaluation methodology goes beyond traditional accuracy metrics—we analyze behavioural quality, reasoning robustness, consistency, bias, and adaptability. This ensures your AI systems are dependable and ready for deployment.

Why AI Testing Matters

Modern AI agents interact, decide, generate content, and automate tasks.

Prevent Unpredictable Behaviour

AI agents may produce unexpected or harmful outputs when faced with unusual queries. Testing ensures stable, controlled, and reliable behaviour.

Eliminate Hidden Failures

Without evaluation, agents can fail silently—producing incomplete, incorrect, or unusable results without clear signals. Testing exposes these weaknesses early.

Reduce Bias & Safety Risks

AI systems can unintentionally introduce bias or generate unsafe content. Rigorous testing identifies these issues before they reach end-users.

Improve Consistency Across Use Cases

Agents often behave differently depending on context or user input. Testing guarantees predictable, repeatable performance across scenarios.

What We Evaluate

AI systems require more than just accuracy—they need to behave reliably, safely, and intelligently across real-world scenarios. Our evaluation framework measures how your agent thinks, responds, and adapts, ensuring it performs effectively under diverse conditions.

Functional Performance

  • Response accuracy

  • Task completion reliability

  • Context understanding

  • Adherence to instructions

Robustness Under Stress

  • Handling ambiguous or tricky prompts

  • Resistance to adversarial inputs

  • Error recovery ability

  • Stability across repeated queries

Safety & Ethical Behaviour

  • Bias and fairness checks

  • Toxicity and safety compliance

  • Ethical response alignment

  • Hallucination detection

User Experience Quality

  • Clarity and tone of responses

  • Personalization when appropriate

  • Response structure and coherence

  • Speed and interaction smoothness

Agent Evaluation Framework

Benchmarking

We use standardized tests and custom benchmarks tailored to your domain:

  • Reasoning suites

  • Knowledge tests

  • Domain-specific evaluation datasets

  • Scenario-based challenges

Real-World Simulation

We simulate real user behaviour:

  • Confusing queries

  • Multi-intent prompts

  • Shifting context

  • High-pressure scenarios

  • Long conversations requiring memory

Human-in-the-Loop Review

Experts analyze agent outputs for:

  • Coherence

  • Factual accuracy

  • Safety

  • Action justification

Scoring & Insights

You receive:

  • Detailed evaluation reports

  • Weakness identification

  • Improvement recommendations

  • Scorecards for each capability

Ready to start creating an amazing world?