The Runtime
    Policy Layer
    for AI Agents

    Enforce consistent AI agent security policies across every model, cloud, and agent framework, without SDKs or code changes.

    Security & Compliance
    Token Control
    Your Custom Rules

    Your technology stack can change. Your policy stays consistent.

    Skyrelis Agent Profile dashboard showing policies configured, tools used, risk score, and the agent activity map
    0%
    of agent actions evaluated
    before execution
    360min
    to first enforced policy in production
    1000lines
    of agent code required to change
    5layer
    that owns runtime action control

    AI Agents Are Moving
    From Chat to Action

    Each stage up the autonomy ladder creates more value, and more runtime risk. Security must evolve from "who has access?" to "what is the agent allowed to do?"

    💬
    Stage 1
    Chatbot
    Answers questions. No tools, no system access. Risk is low.
    Low risk
    ✍️
    Stage 2
    Copilot
    Drafts and suggests. A human approves every output.
    Moderate risk
    🤖
    Stage 3
    Agent
    Calls real tools, reads live data, writes to systems. Actions have consequences.
    Higher risk
    ⚡
    Stage 4
    Action Workflow
    Triggers business actions at scale — payments, CRM writes, emails — fully autonomously.
    Runtime action control required
    Lower runtime risk
    Higher runtime risk

    Your Existing Controls
    Don't Reach the Runtime

    They're necessary, but none of them govern what an agent does once it's running.

    🔑
    IAM / RBAC
    Controls who has access
    🛡
    DLP
    Protects data at rest & in motion
    🔒
    AppSec
    Secures the application perimeter
    📋
    Compliance
    Proves company-level controls
    💬
    LLM Guardrails
    Filters prompts and outputs
    ⚠ None of these control what the agent actually does at runtime
    ↓
    Beyond Prompt Guardrails
    Control What the Agent Sees, Decides, and Does
    Prompt guardrails are essential, but they only address part of the risk. Skyrelis protects the full agent workflow, from prompts and model responses to tool calls, API requests, data access, approvals, and actions.
    Inspect prompts and outputsControl tool and API accessProtect sensitive dataRequire human approvalCapture complete audit evidence
    ↓
    The Missing Layer
    Action Control —
    Not Just Access Control
    Access control governs who can authenticate. Action control governs what the authenticated agent is allowed to do. Skyrelis enforces hyper-specific policy per agent, per customer, per action — decoupled from your application code. Define rules in plain English. Enforce everywhere. Change without a redeployment.
    Hyper-specific policy per agent, per customer, per action
    Policy lives in Skyrelis — not buried in application code
    Context-aware enforcement: mission, tool scope, data sensitivity
    Human approval gates before high-risk actions execute

    “As we bring our CRM agent to more enterprise customers, each customer has different requirements for what information can be shown, redacted, or blocked, and what actions the agent can take. Skyrelis helps us support those differences without custom building or configuration sprawl for every customer, so we can ship features faster and expand our use cases while keeping our engineering team focused on improving the core product.”

    Daniel CastroCEO, Persona X
    Read the Persona X case study →

    “Enterprises spent the last two years proving agents can do the work. What they still can't prove is what an agent actually did, why it was permitted to, and what stopped it when it went wrong. Identity and access management governs who an agent is — nothing governs what it does at machine speed. That missing control layer is the difference between an agentic pilot and an agentic deployment, and it is the problem Skyrelis is building for.”

    Evan SolomonCEO, EFS Networks

    “Empromptu helps engineering teams rapidly build production-ready AI applications, while Skyrelis gives security teams the independent runtime controls they need to confidently deploy those applications in highly regulated environments. Together, we're helping SaaS companies deliver enterprise-ready AI without compromising innovation or security.”

    Shanea LevenCEO and Co-founder, Empromptu
    Read the partnership announcement →

    Skyrelis has been accepted into NVIDIA Inception, NVIDIA's global startup program for companies building on AI, accelerated computing, and data science. Membership gives us closer access to the tooling, technical resources, and ecosystem shaping the infrastructure where enterprise agents run.

    Read the NVIDIA Inception update →

    Every Agent Action.
    Evaluated in Real Time.

    Skyrelis sits inline between your agents and everything they reach — models, tools, APIs, data. Every call is evaluated before it completes. Explore the full platform →

    Skyrelis Runtime Proxy — Inline Policy Enforcement
    Agent FleetLangChain · CrewAI · CustomAgentic AppsEnterprise · Vendor-built☁ SKYRELISPolicy EnforcementInline Proxy✓ Allow✗ Block↳ Escalate🗄 APIs & Tools🤖 LLM Models☁ Data SourcesFull audit trail ▸

    Resources

    Tools and guides to help you assess, secure, and govern your agent fleet.

    🎯
    Request a Demo
    See live policy enforcement on a real agent workflow. 30 minutes. No slides. Policy running in production before the call ends.
    Book a Demo →
    💰
    ROI Calculator
    See what agentic risk is costing you. Answer a few questions about your agent fleet and get a personalized estimate of breach costs avoided, compliance exposure reduced, and security hours recovered.
    Calculate Your ROI →
    📊
    Agentic Security Scorecard
    8 questions every security team should answer about their agent fleet. Free. Results in minutes. Know exactly where your gaps are.
    Get the Scorecard →