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    Kriv AI

    AI-101 & Glossary

    Plain-English explanations of the AI and automation terms that matter in regulated industries.

    This page is designed for leaders and teams in healthcare, life sciences, and other regulated sectors. It explains the language we use around governed AI, agentic automation, and MLOps—without assuming a data science background.

    • No jargon for jargon's sake—clear, practical definitions.
    • Focused on risk, governance, and real-world workflows.
    • Linked directly to solutions, use cases, and deeper resources.

    Nothing here is legal or regulatory advice. It's a practical companion to conversations with your counsel and risk teams.

    Start with These Core Concepts

    Agentic AI

    AI systems that can take autonomous actions using tools and workflows to accomplish complex tasks.

    Why it matters: In regulated industries, agentic AI must have clear governance, human oversight, and audit trails.

    Explore Agentic AI Solutions

    AI Readiness & Governance

    The organizational capability to deploy AI responsibly with proper oversight, policies, and infrastructure.

    Why it matters: Without readiness assessment, organizations waste resources on pilots that never reach production.

    Learn About AI Readiness

    MLOps

    Practices for deploying, monitoring, and maintaining machine learning models in production.

    Why it matters: Healthcare and life sciences need MLOps that includes compliance, audit logging, and drift monitoring.

    Explore MLOps Services

    LLM (Large Language Model)

    AI models trained on vast text data that can understand and generate human-like language.

    Why it matters: In regulated contexts, LLMs need careful fine-tuning, prompt guardrails, and data handling policies.

    LLM Fine-Tuning Services

    PHI / PII

    Protected Health Information and Personally Identifiable Information—data categories with strict handling requirements.

    Why it matters: Any AI system touching patient or personal data must be designed for HIPAA and privacy compliance.

    Security & Compliance

    AI Governance & Compliance

    Frameworks and processes ensuring AI systems meet legal, ethical, and organizational standards.

    Why it matters: Regulators and boards increasingly expect documented AI governance—not just good intentions.

    Governance-as-a-Service

    Governance & Risk

    Agentic AI & Automation

    Data & Infrastructure

    Models & MLOps

    General AI Concepts

    How to Use This Glossary

    It's okay if you don't recognize many terms—that's exactly why this page exists. Here are a few ways to get the most out of it:

    Use it during strategy meetings so everyone shares the same language.

    Share specific terms with colleagues when a concept feels fuzzy.

    Use 'Where this shows up in our work' to connect terms to real projects.

    Explore practical examples in our Use Case Playbook →

    From Definitions to Decisions

    AI-101 FAQs

    Want Help Translating AI Jargon into Your Reality?

    If you're trying to connect these concepts to your own systems, data, and regulatory environment, that's exactly where we can help.