AI & ML
TESTING SERVICES
As AI and machine learning products become central to business operations, quality assurance must evolve beyond functional testing. Astonsys has built specialised frameworks to validate AI systems end-to-end — from training data quality to production model drift monitoring. Our team is trained in LLM testing, responsible AI auditing, and ML model validation, making us the QA partner of choice for companies building AI-powered products.
LLM & GenAI Testing
Prompt injection testing, hallucination detection, output consistency validation, and toxicity testing for products built on GPT, Claude, Gemini, and other models.
ML Model Validation
Accuracy, precision, recall, and F1 benchmarking. Bias detection across demographic segments, edge case stress testing, and model performance analysis.
AI Data Pipeline Testing
End-to-end validation of data ingestion, preprocessing, feature engineering, and model inference pipelines. We ensure your data flows correctly from source to prediction.
Model Drift Monitoring
Continuous production monitoring for data drift, concept drift, and performance degradation. Automated alerts so you know the moment your model starts behaving differently.
Why choose Astonsys for AI & ML Testing?
Traditional QA fails on AI systems. You need specialists who understand model behaviour, data pipelines, and non-deterministic outputs. We help you prove your AI is safe, fair, and auditable — essential for regulated industries and maintaining user trust. From training data quality to production model drift monitoring, we ensure your AI behaves safely and reliably in production.
Specialised AI Quality Services We Offer
Astonsys offers a comprehensive suite of AI & ML testing services to ensure that your intelligent systems are functioning optimally, ethically, and securely.
LLM & GenAI Testing
Prompt injection testing, hallucination detection, output consistency validation, and toxicity testing for Large Language Models.
ML Model Validation
Accuracy benchmarking, bias detection across demographic segments, edge case stress testing, and model performance analysis.
AI Data Pipeline Testing
End-to-end validation of data ingestion, preprocessing, feature engineering, and model inference pipelines.
Model Drift Monitoring
Continuous production monitoring for data drift, concept drift, and performance degradation with automated alerts.
Responsible AI Audit
Fairness testing, explainability (XAI) validation, and regulatory compliance testing aligned with the EU AI Act and ISO 42001.
RAG System Testing
Retrieval accuracy, context relevance, and grounding validation for AI-powered knowledge systems built on RAG.
Tools Used for
AI & ML Testing Service
Our AI testing engineers utilize the industry's most advanced toolchains to validate, monitor, and audit intelligent systems.
