Iron Broad agent workforce and AI governance across any infrastructure.
DataRobot is strong for organizations combining predictive AI, generative AI, agent development, external-asset governance, real-time defense, and private deployment.
← All comparisons
Make durable trust and recovery the runtime foundation.
DataRobot builds, deploys, observes, and governs agents and other AI assets across cloud, private, on-premises, sovereign, and air-gapped environments. Iron Gorilla adds a tighter runtime model for durable work, behavioral trust, approvals, containment, compensation, and recovery.
Control the full action lifecycle, not only the AI estate.
DataRobot spans the wider AI estate. Iron Gorilla focuses the operating layer on durable agent state, behavioral Trust Profiles, adaptive autonomy, contextual approvals, MCP health, action compensation, containment, and guided recovery.
Feature comparison
Compare full-stack AI governance with agent-first operations.
Iron Gorilla covers 38 of 42 capabilities. DataRobot Agentic AI covers 29. Iron Gorilla includes 13 capabilities DataRobot Agentic AI does not.
Managed agent runtimeBuild, run, supervise, and improve agents in one platform.11 features
Fully managed production agent runtimeDeploy, execute, scale, and operate production agents as one accountable service.
Guided Agent BuilderCreate reviewed, versioned agents without assembling the runtime by hand.
Durable execution across interruptionPreserve state and continue long-running work after workers, networks, or providers fail.
Managed long-term agent memoryKeep governed context across sessions and long-running goals.
Long-running goal managementTrack plans, dependencies, state, and outcomes across many steps or sessions.
Managed multi-agent orchestrationCoordinate specialized agents, dependencies, handoffs, and shared work.
Contextual human approval gatesPause higher-risk work for a named person before execution continues.
Checkpoint resume and operator replayRestart work from a known good state after review or failure.
Business-action compensationReverse or compensate for a completed business action during recovery.
Scheduled and event-triggered agentsStart governed work from schedules, APIs, events, or enterprise systems.
Runtime observability and tracesInspect agent steps, tools, models, latency, failures, and outcomes.
Policy and evidenceControl actions before they happen and keep proof of each decision.11 features
Pre-action business policy enforcementEvaluate business rules before tools change enterprise systems.
Policy simulation before activationTest expected decisions against sample actions before enforcement.
Prompt, output, and sensitive-data controlsInspect model traffic and prevent unsafe content or sensitive-data exposure.
Tool permissions and action allowlistsRestrict which tools and actions each agent may use.
Behavioral Trust ProfilesScore each agent from observed behavior and surface drift to operators.
Adaptive autonomy from earned trustTighten or relax oversight as observed behavior changes.
Live agent and connection containmentIsolate risky agents, connections, or work before impact spreads.
Guided operational recoveryDiagnose failure and recover affected work through an accountable operator flow.
Tamper-evident action audit trailPreserve policy, approvals, calls, actions, and outcomes as trustworthy evidence.
Scheduled fixed reports and portable exportsGive leaders and auditors repeatable reports in stable formats.
Governance for externally built AI assetsApply monitoring, policy, security, and compliance to agents and apps built elsewhere.
Connections and modelsControl MCP tools, model traffic, routing, cost, and integrations.9 features
MCP tools and connectionsConnect agents to MCP servers and governed enterprise actions.
MCP ownership, health, and lifecycleOperate connections with owners, credentials, health, risk, assignments, and history.
Enterprise application integrationsConnect agents to existing systems without rebuilding every interface.
APIs and developer interfacesEmbed agents and platform functions into existing products and workflows.
Multiple model providersUse approved models across providers without rebuilding agent workflows.
Policy-aware model routingSelect models by capability, cost, latency, risk, and policy.
Automatic model-provider fallbackContinue work on an approved backup when a provider fails.
Spend attribution, budgets, and cost routingTrack model cost by agent and constrain or reroute work before spend runs away.
Per-agent tool and model assignmentGive each agent only the tools, data, and model routes it needs.
Enterprise and governmentProtect identity and data across private and public-sector work.11 features
Managed SaaS deliveryUse the platform as a supported enterprise cloud service.
Customer-controlled on-premises deploymentOperate the platform inside infrastructure controlled by the buyer.
Air-gapped deployment patternOperate inside disconnected environments with controlled data and model access.
Enterprise identity and scoped accessApply organization, role, group, environment, and ownership boundaries.
Published plan structureShow buyers public plan options and included capabilities.
Dedicated government and defense solutionAddress mission, procurement, deployment, approval, and evidence needs directly.
Regulatory and assurance mappingsMap controls and evidence to regulated or public-sector assurance needs.
Formal implementation partner ecosystemUse consulting, technology, and delivery partners for adoption.
Independent SOC 2 Type II assuranceProvide independent assurance that service controls operated effectively over time.
Predictive and generative AI lifecycle platformManage predictive models, generative applications, agents, and data science assets together.
Forward Deployed Engineer delivery modelUse vendor engineers to build and deploy mission-critical agents with the customer.
The short answer
DataRobot Agentic AI or accountable agent operations?
Use DataRobot when predictive models, generative applications, agents, external assets, red teaming, compliance, monitoring, and private or air-gapped deployment need one governance platform.
Choose Iron Gorilla when durable runtime state, behavioral trust, adaptive autonomy, contextual approvals, MCP health, action compensation, containment, and guided recovery are the main requirement.
Switch with less risk
Already under contract with DataRobot Agentic AI?
Your organization may qualify for a contract buyout and complimentary professional services when it moves production agent operations from DataRobot Agentic AI to Iron Gorilla.
Check eligibilityFAQ
DataRobot Agentic AI alternative questions
Is Iron Gorilla an alternative to DataRobot Agentic AI?
Yes. Both platforms support production AI work. DataRobot Agentic AI does build and run production agents, but its wider AI lifecycle platform does not publish the same checkpointed business-action continuity, earned behavioral trust, or compensation model. Iron Gorilla adds a managed operating model centered on durable execution, behavioral trust, action control, containment, and recovery.
What is the main difference between DataRobot Agentic AI and Iron Gorilla?
DataRobot spans the wider AI estate. Iron Gorilla focuses the operating layer on durable agent state, behavioral Trust Profiles, adaptive autonomy, contextual approvals, MCP health, action compensation, containment, and guided recovery.
Does DataRobot Agentic AI run production agents?
does build and run production agents, but its wider AI lifecycle platform does not publish the same checkpointed business-action continuity, earned behavioral trust, or compensation model.
Where is DataRobot Agentic AI stronger?
DataRobot is stronger for broad predictive and generative AI lifecycle management, external-asset governance, automated compliance, red teaming, Forward Deployed Engineering, and infrastructure portability.
When should a team choose Iron Gorilla over DataRobot Agentic AI?
Choose Iron Gorilla when durable runtime state, behavioral trust, adaptive autonomy, contextual approvals, MCP health, action compensation, containment, and guided recovery are the main requirement.
Can Iron Gorilla buy out a DataRobot Agentic AI contract?
Your organization may be eligible for a contract buyout and complimentary professional services. Eligibility and scope depend on your current contract and migration needs.
See the full agent lifecycle.
Build an agent. Set its limits. Run it with trust, approval, and audit controls.
Book a demo