Speed and intelligence are both expected from modern enterprise applications. But delivering AI-enabled features without compromising timelines, budgets, or quality continues to be a challenge for most teams. At DBiz, we work with enterprises to solve this problem using OutSystems, a leading low-code platform that makes it possible to build scalable, intelligent applications in a fraction of the time traditional approaches demand. 

With native support for integrations, visual workflows, and AI-assisted development, OutSystems aligns with the practical realities of building and deploying enterprise-grade solutions at speed. 

There’s growing demand for AI across industries, but implementation often stalls due to fragmented teams, long build cycles, and complex infrastructure. Even relatively focused use cases like lead scoring or automated support tend to require specialized roles, backend changes, and extensive testing before anything goes live. 

We have seen first-hand how AI features are often scoped in but delayed until “phase two.” By then, priorities shift and momentum is lost.  

OutSystems helps eliminate those delays. We use it to design modular applications, integrate AI services, and iterate quickly across client environments. Its visual environment, reusable components, and built-in security allow teams to move faster without cutting corners. Here’s what that translates to for enterprise leaders: 

• Shorter time to market for AI-enabled features 
• Leaner teams with less dependency on niche roles 
• Easier governance across development and deployment 
• Infrastructure that’s flexible enough to adapt as AI capabilities evolve 

It aligns perfectly with the pace and priorities of businesses looking to move quickly without compromising on quality or performance. 

We work with a range of AI tools that integrate well into OutSystems applications, depending on the business need and cloud ecosystem in place: 

• OpenAI APIs for advanced chat, summarization, or language-based logic 
• Azure Cognitive Services for OCR, speech recognition, and sentiment analysis 
• TensorFlow for custom prediction models tailored to internal datasets 
• AWS AI Services where clients operate within the AWS environment 
• OutSystems AI Assist for productivity gains during the build process 

These tools are plugged in through APIs or connectors, and OutSystems makes it easy to bring them into the application logic without introducing fragility or technical debt. 

AI is most valuable when embedded in operational workflows. With OutSystems, we help clients build applications where AI works in the background to support better decisions and smoother user experiences. 

• Risk analysis and decision support: Scoring models highlight anomalies or approvals that need attention 
• Customer-facing automation: Virtual assistants guide users, collect data, and reduce pressure on support teams 
• Document and data processing: AI extracts key data from forms or reports, reducing manual input and errors 
• Developer productivity: Inline code suggestions improve consistency and cut development time 

These features are embedded into the application from the start, forming part of the complete experience.  

Building AI-enabled apps in a low-code platform like OutSystems is faster, but that speed can also surface hidden delays if the process isn’t structured right. Based on how we typically work with enterprise teams, there are a few areas where time is often lost — and how we usually address them: 

• Rushing into model selection before clarifying business logic 
  We’ve seen teams start with the AI tool instead of the problem. That adds rework later when outputs don’t fit the workflow. We flip that: define the decision points first, then bring in the right service or model. 
• Underestimating production-readiness tasks 
  Once a model works in testing, teams often assume it's ready. But integration, error handling, and post-deployment monitoring are where delays creep in. We build these in as part of the sprint, not as cleanup after. 
• Scattered ownership across business and tech 
  Without clear alignment between product owners and tech leads, even fast platforms stall. We structure working groups with shared KPIs across both, so delivery doesn’t get stuck in sign-off loops. 

Low-code accelerates delivery, but only when paired with the right working model. That’s where we spend just as much time as we do on tools or features.  

OutSystems lowers the barrier to delivering enterprise-grade AI features. At DBiz, we help teams use this flexibility to solve real business problems instead of waiting for long-term digital transformation programs to catch up. 

If you’re looking to add intelligence to your applications without adding complexity, we can help you move from idea to deployment faster.