Lev Agsfer, Author at Pacific AI

Lev Agsfer

Pacific AI Healthcare AI Governance Platform on AWS Marketplace and Azure Marketplace

Pacific AI’s healthcare AI governance platform now available on AWS Marketplace and Azure Marketplace

The Joint Commission's RUAIH Certification: requirements and sustainability for healthcare AI governance

What the Joint Commission’s Responsible Use of AI certification requires, and why automation is how you sustain it

Pacific AI Governance Policy Suite Q2 2026 release notes document with verification checkmark

The Q2 2026 AI Governance Policy Suite Release: Six new state laws and a rewritten Colorado AI Act

Table comparing GPT-5.4, Claude-4.6, and Grok-4.2 on four safety categories with percentage scores and status icons

Pacific AI Gatekeeper detects 14.6-point Inappropriate Content safety gap between GPT-5.4 and Grok-4.2

Continuous testing and monitoring of large language models with Pacific AI experts, illustrating enterprise LLM evaluation, performance monitoring, and responsible AI governance.

Testing Healthcare AI In 2026: A Deep-Dive On 60+ Peer-Reviewed Evaluations For Clinical Tasks, Bias, Safety, And Regulation

Multi-domain red-teaming framework methodology diagram showing the seven-dimension rubric for evaluating safety, robustness, and fairness of medical large language models

A Multi-Domain Red Teaming Framework for Safety, Robustness, and Fairness Evaluation of Medical Large Language Models

From Guardrails to Guardians: Continuous Red Teaming and Holistic Safety for Agentic Healthcare AI — presented by Julio Bonis, Principal Data Scientist at Pacific AI

From Guardrails to Guardians: Continuous Red Teaming and Holistic Safety for Agentic Healthcare AI

Engineering Trust: a governance framework for science communication AI, presented by Pacific AI and Science 2 People

Engineering Trust: A Governance Framework for Science Communication AI

MedHELM and the next phase of open medical AI evaluation, presented with Stanford University

MedHELM and the Next Phase of Open Medical AI Evaluation

MedHELM medical AI evaluation framework: task categorization, benchmark datasets, model evaluation, and community resources

MedHELM and The Next Phase of Open-Source Medical AI Evaluation

LLM evaluation report: AI passed accuracy benchmark but failed robustness, bias, representation, and data leakage tests

LangTest: Six Dimensions Healthcare AI Evaluation Must Cover

AI governance visual illustrating responsible AI practices, connecting risk management, compliance, performance metrics, and organizational accountability.

Why Is Responsible AI Practices Important to an Organization?

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