OutSystems’ New Agent Workbench Makes AI Agents Practical, Scalable, and Enterprise-Ready
OutSystems is on a mission to take AI agents out of the lab—and into the enterprise. The low-code platform leader has launched an Early Access Program for Agent Workbench, a new suite designed to help organizations build, orchestrate, and govern AI-powered agents across departments, workflows, and data systems.
While many companies have been circling the promise of agentic AI, most are stuck in pilot purgatory—held back by tool fragmentation, legacy systems, and disjointed data. Agent Workbench is OutSystems’ answer to that stall-out: a centralized, secure, low-code framework that simplifies the creation and management of intelligent agents at enterprise scale.
Beyond the Pilot Graveyard
“Businesses are excited by AI but drowning in ungoverned tools and stalled pilots,” said OutSystems CEO Woodson Martin. “We built Agent Workbench to shift AI agents from being experiments into true business enablers.”
He’s not wrong. As generative AI evolves into more autonomous and context-aware systems, the complexity of development and integration is ramping up. Most enterprises don’t have the time—or talent—to rewire their stack around every promising new AI model or framework. That’s where Agent Workbench steps in.
OutSystems promises to do for AI agents what it did for app development: abstract away the heavy lifting so that IT teams can move faster and innovate responsibly.
What Is Agent Workbench—and Why Now?
Agent Workbench is not another standalone AI tool. It’s a fully integrated extension of the OutSystems low-code platform, built with enterprise demands in mind: speed, scale, security, and explainability.
Here’s what sets it apart:
- Multi-Agent Orchestration: Build workflows where agents operate in parallel, sequence, or hierarchy—handing off tasks, escalating when needed, and collaborating with humans in real time.
- Unified Data Fabric: Connects to existing OutSystems 11 data, external databases, data lakes, and retrieval systems (like Amazon Kendra or Azure AI Search), grounding agents in context-rich, accurate information.
- AI Model Agnostic: Works with your own custom models or integrates easily with providers like Azure OpenAI and AWS Bedrock. This flexibility avoids vendor lock-in while enabling centralized governance.
- Guardrails and Governance: Real-time monitoring, error tracing, logging, and auditability are built in—critical for maintaining trust and compliance in agentic systems.
- No-Rewrite Integration: Agents can tap into legacy workflows and applications without the need to refactor or rearchitect core systems.
Think of it as a pragmatic bridge between AI ambition and enterprise execution. IT leaders can now embed reasoning agents across business processes without blowing up the existing tech stack—or the security budget.
Why It Matters: The Next Frontier of Low-Code Meets AI
OutSystems is clearly positioning itself as more than just a low-code platform—it’s becoming an orchestration hub for intelligent enterprise systems. This move puts it squarely in competition with platforms like Microsoft Power Platform, UiPath, and ServiceNow, all of which are racing to bring agentic AI into mainstream enterprise adoption.
But unlike many rivals, OutSystems is betting on a full-stack, end-to-end approach: control your data, your models, your workflows—and now, your agents—from one platform.
The early access launch is a strong signal that AI agents aren’t just hype anymore—they’re the next phase of digital transformation, provided enterprises can trust them.
Human-AI Collaboration, Without the Chaos
Agent Workbench isn’t a flashy demo—it’s built for IT teams under pressure to deliver real results without breaking security protocols or creating shadow AI projects. It answers one of the biggest questions facing the enterprise AI era: How do we go fast without losing control?
If OutSystems delivers on its vision, Agent Workbench could help enterprises finally shift from AI experimentation to AI execution—one intelligent agent at a time.
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