AgentVisor™
Containment and Runtime Control · Financial Services
Contain AI Agents.
Control Every External Action.
AgentVisor runs AI agents inside a contained execution environment and controls what they can reach beyond it. When an agent attempts to access sensitive data, invoke a tool, call an internal service, use a credential, or connect to a network, AgentVisor evaluates the attempted action against enterprise policy before allowing or denying it.
AI agents are moving from experimentation into financial operations. As their autonomy increases, institutions need more than visibility into what agents have done. They need an enforceable way to contain agents, control their external actions, and prevent activity that exceeds their authority.
FINRA
SEC Regulation S-P
Enterprise Control Environments
Regulatory Context
FINRA has made clear that its rules remain applicable when member firms use generative AI. Its 2026 Annual Regulatory Oversight Report identifies AI agents as an emerging area of risk, including concerns involving autonomy, scope, data sensitivity, auditability, and interactions with third-party systems.
The Problem: Autonomy Changes the Risk
Traditional access controls were designed for people and deterministic applications. AI agents make decisions at runtime, combine tools dynamically, and take paths their developers may not have anticipated.
Excessive Authority
Agents may inherit application, service-account, or user permissions that exceed what is required for the task at hand.
Unpredictable Actions
Changing context, prompt injection, flawed reasoning, or tool misuse can cause an agent to attempt actions outside its intended function.
Sensitive Data Exposure
Agents may attempt to retrieve, combine, or transmit customer, account, trading, or proprietary information beyond their authorized access.
Accountability Gaps
Application logs may show that an action occurred without showing which agent attempted it, what authority was evaluated, which policy applied, or why the action was allowed.
The AgentVisor™ Approach
AgentVisor combines contained execution with policy enforcement at the boundary between the agent and external resources.
Contained Agent Execution
Run agents inside a sandboxed environment that limits direct access to networks, credentials, data stores, tools, and external services.
Policy-Enforced Boundary
Every attempt to act outside the contained environment is evaluated against enterprise-defined policy before it is allowed to proceed.
Complete Agent Visibility
See which agents are operating, what external actions they attempt, which resources they try to reach, and whether each action is allowed or denied.
Defensible Audit Evidence
Record the acting principal, attempted operation, target resource, relevant context, applicable policy, and enforcement outcome.
Authority Is Not Determined by Agent Reasoning
Prompts can be manipulated. Models change. Agents can take paths their developers did not anticipate. AgentVisor contains the agent and enforces enterprise policy at the boundary. The agent can determine what action to attempt. It cannot determine whether that action is authorized.
Intelligence decides what. Authority decides whether.
AgentVisor™
Containment and Runtime Control · Financial Services
Containment With Continuous Authorization
AgentVisor controls what AI agents can access beyond their contained execution environment. Every attempted external action is evaluated against enterprise policy, allowed or denied, and recorded with its decision context.
How It Works
1
The Agent Operates Inside Containment
The agent runs inside a sandboxed environment without unrestricted access to external networks, credentials, data, tools, or services.
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2
The Agent Attempts an External Action
The agent attempts to retrieve data, invoke a tool, call a service, use a credential, or reach another resource outside the contained environment.
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3
AgentVisor Evaluates the Attempted Action
AgentVisor evaluates the action against policy using the acting principal, attempted operation, target resource, and relevant context.
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4
AgentVisor Allows or Denies the Action
If policy permits the action, AgentVisor allows it to proceed. If not, it blocks the action. The attempt, evaluation, and outcome are recorded.
From General Access to Contained, Action-Level Control
Control Area
Conventional Approach
With AgentVisor
Agent execution
Runs within the application environment
Runs inside a contained environment
External access
Broad application or service-account permissions
Evaluated for every attempted external action
Policy
Distributed across prompts and application code
Enforced independently at the containment boundary
Credentials
Available within the execution environment
Brokered outside the agent runtime
Enforcement
Dependent on agent or application behavior
Applied before external action proceeds
Audit evidence
Reconstructed across multiple logs
Attempt, policy evaluation, and outcome recorded together
Built for Financial-Services Control Requirements
Supervisory Control
Establish and document how AI agents are permitted to interact with regulated business processes, data, tools, and systems.
Customer Information Protection
Contain agents and enforce policy before they access or transmit customer, account, trading, or other sensitive information.
Examination and Investigation
Maintain evidence showing what an agent attempted, which policy governed the action, what decision was made, and whether the action proceeded.
Third-Party Technology Risk
Apply the institution’s controls when agents, models, tools, or services originate outside the organization.
Least-Privilege Authority
Give each agent only the authority required for a specific action under the current conditions — not standing access based solely on a broad role.
Control That Remains With the Institution
AgentVisor is designed for deployment within existing on-premises, private-cloud, and hybrid environments. Customer data, policies, agent activity, and decision records remain within the customer-controlled environment. Institutions retain control over where agents execute, where policy is enforced, and where operational evidence is stored.
Move From Observing Agents to Containing and Controlling Them
AgentVisor gives financial institutions an enforceable way to contain autonomous systems and control every action they attempt beyond the containment boundary.