We design and build custom machine learning and deep learning models tailored to your business challenges, using state-of-the-art architectures and training workflows.
We fine-tune pre-trained models on your proprietary data to improve performance, adapt to domain-specific language, and meet your exact accuracy or behavior requirements.
We create, curate and annotate high-quality datasets that fuel model training and evaluation, ensuring data diversity, relevance, and compliance with your goals.
Systematic testing of AI-powered applications to ensure accuracy, robustness, alignment, and regulatory compliance. Includes evaluation for edge cases, hallucinations, performance across languages, and adversarial scenarios.
Continuous tracking of AI systems in production to detect performance degradation, bias drift, unusual behavior, or changes in real-world data. Includes alert systems, retraining triggers, and compliance logging.
Quality assurance for applications that embed AI components. Combines traditional software testing with AI-aware strategies to validate functionality, performance, and reliability of AI-driven workflows, APIs, and user interfaces. Ensures consistent behavior even when AI outputs are variable or unpredictable.
