AI Governance
Identity, policy, guardrails, rights and approvals.
From AI Intent to Controlled Enterprise Execution
JupitoSecure AI uses the broader security fabric to govern how AI agents and workflows interact with data, applications, APIs, tools, browsers, workspaces and infrastructure.
The AI Brain identifies the appropriate workflow. The workflow defines how execution should occur. Policy determines whether execution is permitted.
Enterprise AI introduces a new security problem. The question is no longer simply who can use AI, but what the AI can access, what data it can use, which tools it can invoke, which applications it can operate and which workflows it can execute.
Access control alone does not determine what an AI agent can actually do after access is granted.
JupitoSecure applies identity, policy, DLP, rights, approvals, controlled workflows and audit to AI-driven execution.
DLP and Data/IP protection extend across the entire chain: PROMPT → CONTEXT → DATA → TOOL → AGENT → EXECUTION → RESPONSE
Govern AI intelligence, agents, tools, data, execution environments and the resulting actions.
Identity, policy, guardrails, rights and approvals.
Workflow discovery and workflow selection.
Use approved workflows for repeatable enterprise tasks.
Govern AI agents and their interaction with enterprise systems.
Control MCP-based tool discovery and invocation.
Control which tools and APIs an agent can use.
Govern AI-driven browser workflows.
Connect AI execution with controlled workspaces and AI/GPU environments.
Protect prompts, context, data and enterprise intellectual property.
Execute approved tasks through controlled execution environments.
Record execution, tool, policy, access and response events.
Build governed AI execution from intelligence and workflow selection through tools, agents, runtime and audit.
AI intelligence layer for identifying appropriate workflows.
Controlled gateway for MCP-based agent and tool interaction.
Managed services for exposing and governing MCP capabilities.
Approved enterprise tools that can be made available to governed agents.
Shared services for identity and context, policy and guardrails, rights, approvals, data entitlements, tool permissions, resource permissions, controlled runtime, DLP, Data/IP protection, response sanitization, audit and enterprise integration.
The AI Brain does not have to perform every enterprise task through unrestricted reasoning. Intelligence can identify the appropriate workflow while execution remains controlled.
For suitable repeatable tasks, workflow-driven execution can reduce unnecessary inference and AI/GPU overhead while making execution more predictable and repeatable.
MCP enables AI systems to interact with external tools and services. JupitoSecure introduces governance around that interaction.
Establish the identity associated with the interaction.
Determine the rights available to the requesting actor.
Control which data can participate in the interaction.
Control which tools can be discovered and invoked.
Associate tool execution with an approved workflow.
Require authorization where the workflow demands it.
Record the resulting tool and execution events.
MCP and tool execution become part of the enterprise security model rather than an uncontrolled extension of AI capability.
An AI agent may be capable of performing actions across multiple enterprise systems. JupitoSecure governs the agent before execution.
Apply controls around identity, roles, rights, data access, tool access, resource access, workflow eligibility, approvals, runtime and audit.
Control the identity and role associated with the agent.
Control which enterprise data the agent can access.
Control which tools are available to the agent.
Control which enterprise resources can be reached.
Determine which workflows the agent is permitted to execute.
Introduce authorization and controlled execution environments.
AI security cannot stop at the prompt. Sensitive information may appear throughout the execution lifecycle.
Protect sensitive information submitted through prompts.
Control sensitive information included in AI context.
Protect enterprise information retrieved for execution.
Control information passed into enterprise tools.
Protect sensitive information maintained during execution.
Apply controls to resulting enterprise data.
Apply response sanitization and data protection.
JupitoSecure separates AI capability from authorization. An agent may identify an action, but execution can depend on eligibility, rights and approval.
Sensitive or consequential workflows can incorporate authorization before execution.
AI governance requires more than recording that an AI service was accessed. Audit should connect the execution to identity, policy, tools and workflow.
Record execution activity.
Record tool interaction.
Record policy decisions and enforcement.
Record access activity.
Record resulting response activity.
AI & Agent Execution can connect to the systems, applications and controlled environments required by enterprise workflows.
Connect governed workflows to approved enterprise APIs.
Connect governed agents to approved MCP capabilities.
Allow approved workflows to interact with applications.
Govern AI-driven browser workflows.
Connect AI execution with controlled workspaces.
Reach approved private resources through controlled access.
Integrate execution and security events with SIEM.
Allow agents to perform useful work under controlled permissions.
Role • Rights • Approval • Audit
Control which tools agents can discover and invoke.
MCP • Tool Policy • Authorization • Audit
Protect enterprise information throughout AI execution.
DLP • Data/IP Protection • Policy
Use AI intelligence to identify an approved workflow rather than relying on unrestricted reasoning for every execution step.
AI Brain → Workflow → Execute
Provide controlled AI development and execution environments.
Workspace • GPU • Data • Tools
Allow governed agents to interact with approved applications, APIs and enterprise systems.
AI execution does not operate as an isolated product. It connects with the broader JupitoSecure platforms through the common security model.
Provide controlled AI and GPU execution environments.
Govern browser-based AI access and workflows.
Isolate risky web-enabled AI execution.
Allow approved agents to reach private APIs and resources through secure outbound connectivity.
All are governed through the common security model.
AI adoption does not need to begin with an enterprise-wide autonomous-agent deployment. Start with one controlled workflow and expand as requirements grow.
Govern identity, policy, data, tools, workflows, agents, execution and audit across the enterprise AI lifecycle.