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    Kriv AI

    For Technology Leaders

    For CTOs & Technology Leaders

    Turn AI pilots, shadow experiments, and ad-hoc automations into a governed, production-grade capability.

    As a CTO in a regulated environment, you're under pressure to "do something with AI"—without breaking security, compliance, or your team's capacity. We help you move from scattered experiments and fragile scripts to a governed AI and automation stack that your C-suite, security, and operations teams can trust.

    Designed for mid-market healthcare, life sciences, and regulated businesses.

    What CTOs Tell Us They're Dealing With

    Sound familiar? These are the conversations we have every week with technology leaders in regulated industries.

    The AI Pilot Graveyard

    You've funded experiments and POCs, but very few have reached stable production. Models live in notebooks, not in your mainline systems.

    Shadow AI & Unruly Automation

    Teams spin up their own scripts, bots, and tools—without review of security, data access, or long-term maintainability.

    Talent & Capacity Constraints

    You don't have unlimited MLOps or AI platform engineers. You need leverage, not more bespoke one-off builds.

    Regulators and Risk Committees Watching

    Every new AI initiative means new scrutiny from security, compliance, and legal. You need patterns you can defend in front of them.

    Integration Complexity

    EHRs, CRMs, data warehouses, queues, automations—nothing lives in isolation. You need AI that respects your architecture, not fights it.

    This page is designed to show how we help you address exactly these issues, step by step.

    How Kriv AI Helps Technology Leaders

    We focus on outcomes that matter: governed production, architecture alignment, and repeatable patterns.

    From Pilots to Governed Production

    We help you evaluate existing AI pilots and experiments, identify what's salvageable, and define a roadmap for stable, governable deployment.

    AI Readiness & Governance Assessment

    Architecture-Aligned Agentic Automation

    We design AI agents and automations that fit into your architecture: APIs, data platforms, Zapier/Power Automate/n8n, and your identity stack.

    Agentic AI & Automation

    MLOps & Governance as a Capability

    We help you move towards a repeatable way of deploying, monitoring, and governing LLMs and AI components, not one-off hero projects.

    MLOps & Governance-as-a-Service

    Goal: Make AI a responsible capability in your org, not a collection of disconnected scripts.

    Three Quick Wins We Typically Look For

    We start with focused, high-value engagements that demonstrate value fast.

    01

    Stabilize One Critical Workflow

    Identify a single high-friction workflow (e.g., clinical documentation summarization, internal ticket triage, or a compliance reporting pipeline) and design an agentic or automation pattern that's stable and auditable.

    02

    Map AI Readiness Across Your Landscape

    Run an AI Readiness & Governance assessment to understand where data is AI-ready, where risk is highest, and which use cases are worth prioritizing.

    03

    Standardize a Pattern for LLM Integrations

    Define a reference architecture for how LLMs and agents can be integrated: data access patterns, logging and guardrails, environment and CI/CD alignment.

    See AI Readiness & Governance Assessment

    Typical Tech Landscapes We Fit Into

    We work with common enterprise stacks and adapt to your existing architecture.

    Microsoft / Azure-Centric Stack

    Azure, Azure OpenAI, Power Automate, Microsoft 365, Dynamics, SharePoint.

    We design agentic workflows and governed AI patterns inside your Microsoft ecosystem.

    Databricks / Snowflake Data Platform

    Databricks or Snowflake as core data platform, feeding LLMs and agents with curated, governed data.

    We help you define AI-ready datasets and integration layers.

    Zapier / Monday / SaaS-Heavy Mid-Market

    Zapier (with Kriv AI as a Zapier Silver Solution Partner), Monday.com, CRMs, finance tools, and ticketing.

    We design multi-step automations where AI is the brain, not a bolt-on.

    n8n & Event-Driven Automation

    n8n, internal queues, APIs, and event-driven workflows.

    We focus on robust error handling, governance hooks, and observability.

    See detailed Developer & Integration Approach

    How We Work with Your Team

    We're a specialist extension of your team, not a replacement for it.

    Co-Design with Your Architects

    We run architecture and workflow design sessions with your architects, security, and operations teams.

    Embed into Your Tooling

    We prefer to work inside your Git, CI/CD, monitoring, and infra-as-code standards rather than introducing opaque side systems.

    Transparent Handover

    We document patterns, configs, and workflows so your teams can maintain and extend them—not be dependent on us forever.

    Governance & Security Alignment

    We proactively invite security, risk, and compliance into the conversation early, not as a final hurdle.

    What You Can Expect as a CTO

    Concrete outcomes from working with us, not vague promises.

    • Clarity on where AI actually makes sense in your environment.
    • A roadmap to move from pilots → governed production.
    • Reference architectures for LLMs, agents, and automations in your stack.
    • Fewer rogue scripts and shadow AI; more standard patterns.
    • Artifacts your security and compliance teams can review and sign off on.
    See our Methodology

    CTO & Technology Leader FAQs

    Common questions from CTOs and technology leaders we work with.

    Want to Turn AI Experiments into a Governed Capability?

    If you're dealing with pilot graveyards, shadow automations, and pressure to "do AI" safely, we can help you define a path from experiments to production that your whole leadership team can stand behind.