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Enterprise security products observe individual layers: devices, networks, clouds, identities, or gateway transactions. AI agents operate across those layers. Forge connects those systems into one AI estate and behavioral record, then applies controls at the network, endpoint, gateway, and application layers.

Agentless first

Use existing firewalls, SASE platforms, and secure web gateways as the primary enforcement layer. Forge for devices is available for local or off-network coverage.

Automatic routing

Redirect supported browser, desktop, API, and MCP traffic to the appropriate Forge gateway without hooks or per-client gateway configuration.

Behavioral context

Connect identity, configuration, model activity, tool activity, and outcomes across complete agent sessions.

AI enablement

Give employees governed access to approved AI while improving adoption, configuration, usage, and cost.

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Comparisons

Endpoint and network security was designed primarily around human-initiated process and traffic activity. Agent activity may be machine-to-machine, span multiple systems, or execute outside the observed control point. Traditional telemetry can show that a process contacted a destination without explaining the model, tool, identity, intent, or surrounding sequence.

Sees

Processes, devices, destinations, and traffic.

Misses

AI-native semantics and behavior spanning sessions, systems, and identities.
Forge advantageForge adds agent, model, MCP, tool, identity, content, and session context. It also compiles broad AI access policy into existing network controls and routes supported traffic for content-aware enforcement.
Cloud security products govern resources, workloads, permissions, and posture inside connected cloud environments. Agents also operate across endpoints, repositories, SaaS applications, external APIs, and third-party tools. Activity involving those external systems falls outside any single cloud provider’s visibility boundary.

Sees

Workloads and resources inside connected cloud boundaries.

Misses

Behavior spanning endpoints, code, SaaS, tools, and external services.
Forge advantageForge connects cloud evidence with endpoint, network, identity, code, SaaS, and runtime activity in one inventory and behavioral record. It preserves the relationship between the cloud workload and the actions it takes elsewhere.
Identity and access management determines who an identity is and what it may access. An authentication or entitlement decision does not reconstruct what an agent subsequently did, the order of its actions, or their downstream effects. A permission check at the beginning of a session says little about the decisions that follow.

Sees

Identities, groups, authentication, and entitlements.

Misses

Actual agent behavior, successive decisions, and resulting impact.
Forge advantageForge uses identity as policy context throughout the session. It attributes model and tool activity to people and workloads, evaluates supported actions as they occur, and connects decisions to sessions, violations, and investigations.
A standalone LLM gateway sees model requests explicitly configured to pass through it. Browser AI, SaaS AI, desktop agents, direct integrations, and MCP activity can remain outside that boundary. Manual gateway configuration must be applied to each client and can be edited or removed by the end user.

Sees

Model requests and responses routed through the gateway.

Misses

Unrouted AI surfaces and context from agents, tools, identities, and systems.
Forge advantageForge combines its LLM Gateway with enterprise discovery and automatic routing. Supported traffic reaches the governed path without hooks, SDK changes, or per-client gateway configuration, while Inventory retains visibility across the wider AI estate.
A standalone MCP gateway evaluates MCP discovery and tool calls routed through it. Risk can emerge from what the agent observed, which model made the decision, what preceded the call, and how the result was used. Direct APIs, hard-coded tools, user-created integrations, and shadow MCP usage can remain outside an explicitly configured gateway.

Sees

MCP servers and tool calls routed through the gateway.

Misses

Shadow usage, non-MCP tools, direct integrations, and risk across a sequence.
Forge advantageForge combines MCP Gateway enforcement with Registry, discovery, identity, model activity, and normalized sessions. Supported tool traffic can be routed automatically, and each decision is evaluated within the broader agent interaction.

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Behavior

Identity → Configuration → Model activity → Tool activity → OutcomeAgents create risk through sequences, not only individual calls. Forge correlates the complete interaction so policy and investigations can evaluate what the agent is doing over time.
Several permitted actions can become unsafe when combined. Behavioral context supports more precise policy, stronger investigations, and fewer blunt allow-or-block decisions.

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Enablement

The same inventory, identity, routing, and behavioral context provides the infrastructure for expanding AI safely.

Governed access

Publish approved MCP servers and skills, then provide identity-aware self-service access.

Consistent experience

Distribute native configurations and route existing workflows onto governed services transparently.

Continuous improvement

Improve adoption, subscriptions, cost, policies, models, and tools using actual behavior.
Forge turns existing security infrastructure into a foundation for AI adoption, with controls applied at the right layer and continuous improvement based on how people and agents actually work.