OutSystems Agent Workbench Powers Widespread Agentic AI Adoption in Enterprises

OutSystems Agent Workbench has now reached general availability, providing a powerful, low-code platform to accelerate agentic AI adoption across enterprises and simplify how intelligent agents are built, managed, and deployed.

Why Agent Workbench Matters: From Pilot to Production

Many organizations struggle to deploy AI agents at scale due to governance, security, integration, and scalability challenges. With Agent Workbench, OutSystems addresses exactly these issues enabling teams to create AI agents across use-cases, departments, data sets and systems, all from a unified low-code environment.

By offering a governed, enterprise-grade lifecycle for agents including orchestration, human oversight, and compliance the platform helps organizations move from experimentation to real-world business impact.

Early Momentum & Real-World Impact

Since its general availability on September 30, 2025, more than 5,500 AI agents are reported to be in development on the platform.
A fast-growing ecosystem of nearly 1,500 certified developers is building enterprise-grade agentic applications using Agent Workbench.
Notable early adopters include Axos Bank, Thermo Fisher Scientific, and Ascot Insurance, who are using the tool to automate mission-critical workflows.

Some highlighted use cases:

Axos Bank developed an intelligent log-analysis agent to interpret error logs and give real-time recommendations, reducing manual effort.
Thermo Fisher Scientific built a Customer Escalation Agent that processes unstructured customer interaction data to automate triage and speed up issue resolution.
Ascot Insurance created an agent to analyze agent activity logs and determine KPIs by parsing unstructured data, which was previously difficult or impossible to assess.

Key Capabilities of Agent Workbench

Low-Code Agent Building
The platform allows developers and business users alike to create intelligent agents, reasoning over real-time goals, decision-making, and action without complex AI engineering.
Full Lifecycle Orchestration
Agent Workbench supports the entire agent lifecycle from design to deployment, monitoring, and management with built-in governance, security, and auditability.
LLM Flexibility
The platform supports a wide range of models and providers: Bedrock, Azure OpenAI, Anthropic, Gemini, Cohere, Mistral, Databricks, AI2, IBM watsonx, Vertex AI, and Hugging Face. Teams can connect a model once and reuse that integration across multiple agents without rewriting.
Open Ecosystem & Agent Marketplace
OutSystems is building an open ecosystem of agentic applications. Pre-built agents are available for common workflows scheduling, task automation, knowledge management helping accelerate deployment.
Developer Enablement
As part of its launch, OutSystems has trained and certified nearly 1,500 developers on Agent Workbench, helping scale agentic AI adoption across its customer base.

Strategic Impact & Business Value

Scalable Agentic Transformation: Agent Workbench helps move organizations from AI pilots to scalable, multi-agent deployments, reducing reliance on point solutions.
Increased Operational Efficiency: By automating repetitive tasks and orchestrating multi-agent workflows, enterprises can boost efficiency and reduce manual burden.
Trusted AI at Scale: With built-in governance and auditability, businesses gain confidence in deploying intelligent agents in production scenarios.
Cross-Functional Innovation: The platform bridges business domains allowing AI agents to work across systems, departments, and data, unlocking new use cases.
Accelerated Time-to-Value: Low-code development + model flexibility = faster deployment and iteration, driving ROI sooner.

Challenges and Considerations

Data and Integration Complexity: To maximize value, organizations need to connect agents to clean, integrated data sources spread across legacy systems.
Governance Policies: Defining guardrails, access controls, and audit processes for agent behavior is critical to maintain trust and compliance.
Change Management: Teams must adapt to building and working with agentic systems, not just using traditional applications.
Model Selection: Choosing and optimizing LLMs for different agents (e.g., cost vs latency) requires thoughtful planning.

Future Outlook

OutSystems Agent Workbench represents a major step toward realizing enterprise-scale agentic AI transformation. As more organizations adopt the platform, we are likely to see:

Broader adoption of multi-agent workflows across core business operations.
Pre-built agent templates accelerating time-to-value for common enterprise use cases.
Richer orchestration, monitoring, and governance features, enabling robust management of large agent fleets.
Stronger collaboration between human operators and AI agents, unlocking new productivity gains.

Conclusion

With the general availability of Agent Workbench, OutSystems is positioning itself at the forefront of the agentic AI revolution. By providing a secure, low-code platform to build, orchestrate, and scale AI agents, OutSystems empowers businesses to harness the full potential of intelligent automation not as a series of experiments, but as a transformational, production-ready capability.

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