FAQs
Q) What is LLM risk evaluation and why does it require continuous monitoring?
LLM risk evaluation is the ongoing measurement of a large language model's production behaviour — hallucination rates, prompt injection susceptibility, output accuracy drift, bias patterns, and OWASP Top 10 LLM risk exposure. It requires continuous monitoring because LLMs do not remain static after deployment. They encounter input distributions they were never validated against, can be updated by vendors without notification, and generate probabilistic outputs that shift as context changes. Point-in-time validation cannot govern a system that changes continuously.
Q) Does the EU AI Act apply to GenAI and LLMs already deployed?
Yes. The EU AI Act introduces GPAI model obligations that are already live, including adversarial testing, incident reporting, and technical documentation requirements. Enterprises deploying GPAI models in high-risk contexts — credit scoring, healthcare, employment, critical infrastructure — face additional obligations including continuous risk management and real-time human oversight. Finland activated EU AI Act enforcement powers in January 2026. The August 2026 deadline covers high-risk AI systems under Annex III.
Q) What is AI evidence management and how is it different from AI documentation?
AI documentation is produced at specific points in a system's lifecycle — at design, at deployment, at validation. AI evidence management is the continuous, automated generation of operational records that prove how AI systems are behaving right now. The distinction matters when a regulator requests the specific model version, data inputs, output, and accountable owner for a decision made three months ago — documentation requires reconstruction; evidence management produces the record immediately, because it was generated as the decision was made.
Q) How is Adeptiv AI different from standard AI governance platforms?
Standard AI governance platforms govern AI through documentation, policy workflows, and periodic assessments. Adeptiv AI is operational AI governance infrastructure — auto-discovering AI systems, evaluating LLMs continuously in production, computing compliance from live behaviour across 40+ regulations, enforcing policies at the runtime layer, and generating audit evidence automatically. The difference is not a feature comparison. It is a governance philosophy: documentation versus operation.
Q How long does it take to implement Adeptiv AI governance infrastructure?
Implementation timelines vary by AI environment complexity and the number of AI systems under governance. Adeptiv AI connects to existing infrastructure through APIs and integration layers — it does not require replacement of current systems. Contact the Adeptiv AI team for a governance readiness assessment scoped to your specific environment and regulatory obligations.
