Configuration time
Define policies, schemas, and datasets. Configure guardrails, access controls, and monitoring rules before anything runs.
For engineers and AI platform teams
The AI governance platform for the agents you build and the AI your team uses
Track every model, agent, and decision for agents running on the platform. Enforce policies in real time and keep a record of each check.
What AI governance oversight means
AI governance oversight gives each governed AI system visible activity, a named owner, recorded policy decisions, and evidence teams can review after every action. SUPERWISE® AMP brings that oversight into one control plane across Sentinel, Chat, and governed agents.
A runtime control layer between your AI apps and LLMs
SUPERWISE AMP, the Agentic Management Platform, sits between AI applications and underlying models, acting as a control plane that governs, observes, and enforces policies across your entire AI environment.
It is the AI governance platform underneath SUPERWISE Sentinel, the AI gateway, SUPERWISE Chat, and the agents you build. Every Sentinel, Chat workspace, and agent reports to the same platform, so one set of policies and one audit trail cover all of them. Runtime guardrails apply configured policy to requests routed through them, and our AI Governance & Controls service helps you write it.
Runtime
On agents built in SUPERWISE, guardrails can check inputs, outputs, or both. Sentinel checks prompts before they leave. Each check is recorded.
Post-runtime
Analytics aggregate performance metrics. Audit trails capture the lineage covered by configured integrations. Dashboards and compliance reports are generated automatically.
How it works
Integrate, govern, and scale your AI operations in three steps.
1Connect
Integrate with your existing AI stack through the REST API or the superwise-api SDK.
2Govern
Define policies, apply guardrails, and control access, all from a single control center.
3Scale
Deploy AI with confidence, with automated compliance and risk management at scale.
Platform capabilities
Core capabilities of SUPERWISE AMP that work together to provide complete AI governance.
Agent Studio
Build and test AI agents with built-in governance and failure detection, then deploy them. Automated testing catches failures before users do.
Guardrails
Runtime protection that checks outputs for configured risks such as PII and jailbreak attempts before they reach users.
Observability
Supporting telemetry that informs governance decisions. Track operational health and detect drift.
Policies
Define what to monitor, when to alert, and how to respond. Define once, enforce across all AI systems.
Integrations
Connect through the REST API or the superwise-api SDK. Register an external agent through Flowise.
Chat
Deploy governed AI chat for business teams, with configurable guardrails, private conversations, and audit trails built in.
Integrations and API
Any framework can call SUPERWISE guardrails through the REST API or the superwise-api SDK.
Register an external agent
Flowise
See SUPERWISE AMP in action
Watch how SUPERWISE provides the governance layer that makes agentic AI safe for production: it prevents unsafe actions, enforces policies, and monitors decisions in real time.
Deployment and operations
SUPERWISE AMP runs as a SaaS service by default, with options for private models and coexistence with your existing AI infrastructure.
SaaS by default
A fully managed service with no infrastructure to provision and no scaling to manage. AMP handles availability, performance, and security; your team configures governance rules and monitors compliance.
Private models and enterprise integration
Govern models running in your own cloud. Prompts stay in your environment; configuration and metadata sync to the SUPERWISE control plane.
Build on SUPERWISE
Three ways to put governance in place. Full patterns and code are in the docs.
Wrap existing LLM calls
Add governance to existing AI apps with the SUPERWISE SDK, without rewriting them.
Deploy governed agents
Build new agents in Agent Studio with governance built in from day one.
Observe and audit
Connect models already in production for observability and audit.
Platform primitives: Agent, Event, Policy, Source, Destination, Dashboard. Composable building blocks for governance, each documented in full. Read the docs
What is agentic AI?
Agentic AI systems pursue goals across multiple steps, use tools, and make decisions without waiting for human approval at each stage. That autonomy creates value and new risk, so SUPERWISE provides the governance layer that makes agentic AI safe for production:
- Full visibility into agent decisions
- Runtime guardrails that constrain behavior
- Human oversight for high-risk actions
- Audit trails for agents running on the platform
- Guardrails on each agent's inputs and outputs
Platform FAQ
Common questions about SUPERWISE AMP
An AI governance platform is the control plane that sets and enforces policy over how an organization uses AI. SUPERWISE AMP, the Agentic Management Platform, sets policy once, enforces it at runtime across every model and agent, and keeps one audit trail for the whole estate.
Agentic AI governance means governing autonomous agents and the models they call, at runtime. SUPERWISE AMP applies policy, guardrails, and an audit trail to the agents you run on it, so agents can run in production while staying inside the rules and leaving a record.
Yes. As the Agentic Management Platform, SUPERWISE AMP manages the full lifecycle of AI agents, from building and configuring them to governing, observing, and controlling them in production, all from one control plane.
The SUPERWISE Agentic Management Platform (SUPERWISE AMP) is the governance control plane for agentic AI. It sits between AI applications and underlying models, providing unified visibility, runtime guardrails, policy enforcement, and audit trails for agents running on the platform.
SUPERWISE AMP is designed for engineers and AI teams building LLM apps and agents who need programmatic control over AI governance. It serves organizations in regulated industries (healthcare, financial services, legal, manufacturing) that require API-first architecture, complete observability, and enterprise-grade control without enterprise complexity.
SUPERWISE AMP provides control through runtime guardrails (PII detection, toxicity filtering, jailbreak prevention), configurable policies that enforce your organization's AI standards, and audit trails for agents running on the platform.
SUPERWISE AMP is a unified Agentic Management Platform with runtime policy enforcement, visibility into agents running on the platform, and API-first architecture for programmatic control.
SUPERWISE AMP is the governance control plane behind SUPERWISE Chat and your other AI systems. Chat is a governed AI workspace built on AMP: Chat executes while the platform governs. AMP provides the policies, guardrails, observability, and audit trails that power Chat and other solutions.
Explore more AI governance resources
Explore AI governance insights, platform resources, implementation guidance, and customer stories.
Services
How our team helps you plan, build, and prove it.
Services
Guardrails
Learn about real-time guardrails and policy enforcement.
Guardrails
SUPERWISE Chat
Governed AI chat for business teams, built on the platform.
SUPERWISE Chat
Pricing
View pricing plans and find the right solution for your organization.
Pricing
Product demo
See the platform and discuss your use case.
Product demo
Flowise integration
Deploy and govern Flowise agents with SUPERWISE.
Flowise integration
Questions buyers ask
All questions- How do you tell real AI governance from theater?Ask five questions, in order: where the data goes, who built the model, whether the controls are enforced while the system runs, what you can see while it runs, and whether you can prove afterwards who did what.
- What can you see while your AI is running?Live usage, cost, and rule triggers, on a screen your own people can open without asking the vendor.
- What can an AI governance layer not do?It bounds what a system may do and records what it did.
Blog
Operationalizing Enterprise AI Governance in 2026: Strategies for Scalable AI Oversight
Learn how organizations can operationalize AI governance in 2026, moving beyond compliance to build trust, manage risk, and monitor AI systems at scale.
AI Observability for Enterprise Governance, Compliance, and Trust
Discover why AI observability is the foundation of responsible AI governance, enabling compliance, transparency, and risk mitigation at scale.
Why Platform-First AI Governance Scales Better Across the Enterprise
Discover how a platform-first approach transforms predictive analytics, improving decision-making and efficiency in manufacturing and construction.
The AI Agent Revolution: Governing the Future of Enterprise Automation
Explore how intelligent AI agents drive enterprise automation, boosting efficiency, safety, and scalability from frontline operations to corporate oversight.
Earlier MLOps webinar recordings
These recordings show the earlier SUPERWISE ML monitoring and MLOps product.
Multi-tenancy architectures for ML
Watch an October 2022 webinar on ML multi-tenancy, isolation models, resource sharing, observability, and architecture trade-offs.
Build continuous ML pipelines with Kubeflow
Watch an October 2022 SUPERWISE® webinar on building Kubeflow pipelines for ML training, Vertex AI deployment, monitoring, and retraining.
Improving search relevance with ML monitoring
Watch an April 2023 webinar on measuring search quality, finding model edge cases, and detecting corrupt data in search systems.
Continuous training with Flyte pipelines
Watch an October 2022 SUPERWISE® webinar on using Flyte pipelines, ML monitoring policies, drift alerts, and automated model retraining workflows.
AI and ML observability platform overview
See how the September 2022 SUPERWISE® platform overview presents AI and ML observability, operational workflows, policies, and telemetry.
Machine learning observability in production
Watch an October 2022 webinar on production ML monitoring, anomaly analysis, data drift, alert policies, and retraining strategies.
Machine Learning Roundup MLOps webinar
Hear SUPERWISE® and Machine Learning Ops Roundup editors discuss production model ownership, ML infrastructure, drift, and model decay.
Building a continuous ML stack
Watch an October 2022 webinar on CI/CD, continuous training, production monitoring, and automation across an MLOps pipeline.
How monday.com monitored marketing ML models
Watch monday.com teams explain how they used SUPERWISE® to monitor marketing ML models, detect drift, and respond to production issues.
Start governing your AI systems in minutes
See how SUPERWISE brings unified governance to your AI operations.