Research Blogs
Always growing with AI insights.
Emerging Trends and Future Directions in LLM Evaluation and Compliance
The rapid evolution of Large Language Models (LLMs) is driving continuous innovation in evaluation methodologies and regulatory frameworks. As LLMs become more powerful and widely used, organizations must stay ahead of emerging trends to ensure responsible and compliant AI deployment.…
How Continuous Monitoring and Re-Evaluation Keep LLMs Safe and Compliant
Deploying a Large Language Model (LLM) is not the end of the governance process. Continuous monitoring and re-evaluation are critical to ensure the model remains safe, effective, and compliant as conditions and data change over time. Continuous monitoring involves tracking…
The Intersection of LLM Testing and AI Safety Regulations
As Large Language Models (LLMs) become integral to critical applications, regulators and industry leaders are prioritizing structured testing as a central component of responsible AI deployment. The EU AI Act classifies high-risk AI systems and mandates rigorous testing before market…
From Lab to Deployment: The Compliance Checklist for LLM Governance
The journey of a Large Language Model (LLM) from research to real-world deployment is complex and requires meticulous attention to compliance. As regulatory expectations evolve globally, organizations must adopt a structured governance framework to ensure responsible AI deployment. A comprehensive…
The Role of Human Oversight in LLM Evaluations and Audits
As organizations increasingly deploy Large Language Models (LLMs) in critical applications, human oversight has emerged as an indispensable safeguard for responsible and compliant AI usage. While automated evaluation tools provide valuable insights, they cannot replace the ethical judgment and contextual…
Explaining LLM Decisions: The Emerging Field of Explainability Metrics
Large Language Models (LLMs) have revolutionized the way information is processed and delivered. However, they are often perceived as black boxes, where even developers cannot easily trace how specific decisions were made. The growing field of explainability aims to address…