Lewes, Delaware, USA
2017
Healthcare, Health Systems, Health Technology, Governance Risk & Compliance, Enterprise Software
Pacific AI is an artificial intelligence company focused on AI governance, validation, and monitoring for healthcare. Its software helps healthcare and life sciences organizations manage the risks associated with developing, purchasing, and deploying AI systems. The platform combines governance automation, model evaluation, regulatory controls, and continuous production monitoring across the AI lifecycle. Pacific AI also maintains testing and policy resources specifically designed for medical and clinical AI.
Pacific AI provides healthcare organizations with infrastructure for governing AI systems from initial assessment through production deployment. Organizations can maintain inventories of AI systems and vendors, conduct risk assessments, generate model cards, test models before release, and continuously monitor deployed systems. Its platform also connects these activities to a regularly updated collection of AI regulations and healthcare-specific frameworks.
The system is designed to automate portions of AI governance work while retaining human review and approval. It can evaluate models for factors including fairness, safety, privacy, robustness, and accuracy, helping teams identify risks before deployment and monitor changes after an AI system enters production.
Pacific AI combines AI governance automation, model testing, and continuous monitoring within a single-tenant software architecture. Governor uses AI to analyze project and vendor documentation, prepare draft model cards, assign proposed risk levels, identify controls, and generate vendor risk assessments for human review.
Gatekeeper provides pre-release evaluation of LLMs, machine-learning models, and agentic systems. Its testing capabilities incorporate MedHELM for clinical AI evaluation and LangTest for accuracy, bias, fairness, and robustness testing. These evaluations can be incorporated into CI/CD workflows so defined test thresholds can act as release gates.
Guardian extends evaluation into production through continuous red teaming and drift detection. It periodically tests deployed systems for changes in safety, bias, privacy, robustness, clinical-task performance, and regulatory readiness.
A notable architectural feature is that Pacific AI deploys inside the customer’s AWS or Azure environment. Governance records and testing information remain within the customer’s cloud tenant, and Pacific AI states that its LLM-as-a-judge capabilities use a proprietary fine-tuned LLM rather than a third-party model API.
Healthcare AI increasingly includes language models, clinical decision-support tools, AI agents, and other systems whose performance and risks can change after deployment. Pacific AI addresses the technical layer between simply documenting governance requirements and testing whether AI systems continue to meet them.
Its approach connects policies, pre-release evaluation, and production monitoring so that governance can operate throughout the AI lifecycle rather than only during an initial review. The combination of healthcare-specific AI evaluation and continuous monitoring makes Pacific AI relevant to the broader movement toward measurable, auditable AI governance in regulated environments.
Governor is Pacific AI’s AI governance and risk-management platform. It maintains information about AI systems, vendors, risks, policies, and controls while automating tasks such as model-card creation and vendor risk assessment. It can analyze uploaded project documentation and generate draft governance materials for review and approval.
Gatekeeper provides pre-release AI testing and validation for LLMs, machine-learning models, and agentic systems. It evaluates areas such as accuracy, fairness, bias, robustness, clinical performance, safety, and regulatory readiness and can integrate testing into CI/CD deployment processes.
Guardian provides continuous production monitoring and red teaming. It runs testing against deployed AI endpoints to identify performance drift, bias, safety issues, adversarial vulnerabilities, and changes in regulatory readiness after an AI system has entered production.
The AI Governance Policy Suite is a maintained collection of AI-related regulations, laws, standards, and frameworks that Pacific AI translates into governance policies and controls. The September 2026 release expanded the suite substantially, including additional healthcare legislation and regulatory material. Pacific AI updates the suite quarterly.
Pacific AI’s technology is primarily used in healthcare and life sciences organizations that develop, purchase, or deploy artificial intelligence. Applications include maintaining inventories of clinical AI systems, evaluating third-party AI vendors, preparing model cards, conducting AI risk assessments, validating medical language models, testing AI before deployment, and monitoring production models for drift or emerging safety problems.
The platform can also support governance of generative AI, machine-learning models, and AI agents used in regulated healthcare environments. Its testing and monitoring infrastructure connects technical evaluation with regulatory and organizational controls rather than treating compliance documentation and model performance as separate processes.
They are the three main components of Pacific AI’s governance platform. Governor handles AI inventory, risk, policy, vendor, and documentation workflows; Gatekeeper tests AI systems before release; and Guardian continuously evaluates systems after they enter production.
Pacific AI uses evaluation tools including MedHELM and LangTest alongside safety and red-team testing. MedHELM provides healthcare-specific clinical evaluations, while LangTest covers areas such as accuracy, bias, fairness, and robustness.
Yes. Guardian runs scheduled testing against production AI systems to detect performance drift, bias, safety problems, robustness issues, and adversarial vulnerabilities that may emerge after deployment.
Pacific AI’s platform is deployed within the customer’s AWS or Azure tenant. The company states that governance records, model cards, risk assessments, test results, and monitoring information remain within the customer’s VPC rather than being stored in a Pacific AI-managed multi-tenant environment.
It is a quarterly updated collection of AI laws, regulations, standards, frameworks, policies, and associated controls designed to help organizations operationalize AI governance. The suite includes both general AI frameworks and healthcare-specific requirements.
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