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Who It's For

AgentVisor™ is for teams deploying autonomous AI agents who need containment, observability, and governance—without sacrificing agent capability.

If your agents act across systems—calling APIs, accessing data, making decisions—and you need to ensure they can't escape their boundaries, you can see what they're doing, and you maintain fine-grained control over their actions, AgentVisor provides the secure runtime to make that possible. Here's how to know if it's right for you.

When AgentVisor Makes Sense​

AgentVisor is a good fit if you:

  • Want capable agents without sacrificing control — Your agents need to call real APIs and access real data, but you can't afford credential leaks or unauthorized access
  • Need access control at every action, not just the front door — Agents make hundreds of autonomous decisions per session, each with its own context (who initiated it, what's being done, on whose behalf). Continuous, contextual policy enforcement at the execution boundary is required.
  • Need to self-host your AI agents — You need control over your infrastructure for cost, performance, or data sovereignty reasons
  • Have compliance requirements — Audit trails, data residency, and governance are non-negotiable
  • Run multi-tenant workloads — Isolation between tenants matters for security and data protection
  • Want defense-in-depth — Container isolation alone isn't enough for your threat model

Use Cases​

Multi-tenant SaaS​

Run customer-provided or customer-specific agent code safely. Each tenant's agents are contained in isolated sandboxes, with full visibility into their behavior and governance over what data and APIs they can access. Perfect for platforms that let customers customize AI behavior.

Enterprise AI​

Your agents need access to internal systems and data to be useful, but that access creates risk. AgentVisor contains agent behavior within boundaries you define, provides visibility into every action, and enforces data loss prevention policies—restricting agents to approved APIs, preventing exfiltration of sensitive data, and maintaining comprehensive audit trails—all without limiting what your agents can accomplish.

Regulated Industries​

Financial services, healthcare, and other regulated industries need audit trails and access controls that can satisfy compliance requirements. AgentVisor provides the observability and policy enforcement needed for SOC 2, HIPAA, and similar frameworks.

Tool-using Agents​

Agents become truly useful when they can invoke tools—calling APIs, querying databases, executing code. But that same capability expands the blast radius of mistakes or attacks. AgentVisor contains tool execution within defined boundaries and provides visibility into every tool invocation, letting agents use their capabilities while you maintain control over how they're used.

Autonomous Workflows​

Long-running agents that operate without human supervision need durability and recovery. Built on Temporal, AgentVisor provides automatic checkpointing so agents survive infrastructure failures and can be horizontally scaled.

Interactive AI Tools​

Developers and power users want to run Claude Code, Cursor, Aider, or shells inside environments with governance. agentvisor exec creates an interactive terminal session inside the sandbox. Every HTTP call flows through the same containment boundaries and is fully observable—the same credential brokering and governance as programmatic agents—without the user needing to configure anything differently.

Multi-Protocol Agent Hub​

Teams that want a single agent runtime accessible to multiple client ecosystems can expose the same agents simultaneously via OpenAPI/REST (LangGraph Agent Protocol), MCP (for Claude Desktop, Cursor, and other MCP clients), and A2A (Google Agent-to-Agent Protocol). AgentVisor handles the protocol translation; agent code stays unchanged.

Other Options​

AgentVisor isn't the only way to run AI agents securely. Here are alternatives to consider:

LangGraph Platform​

If you're using LangGraph and prefer a fully managed service, LangGraph Platform is worth considering. It provides:

  • Managed infrastructure with minimal ops
  • Native LangSmith integration for observability
  • Official support from LangChain

It's a good choice if your primary concern is reducing operational burden rather than maximizing security control.

DIY Self-Hosted​

You can run agent frameworks directly in your own infrastructure without AgentVisor. This gives you maximum flexibility but requires you to build:

  • Your own sandbox isolation
  • Your own policy enforcement
  • Your own audit logging
  • Your own credential management

This approach works for trusted, internal agents where security requirements are lower.

Next Steps​