OutSystems announced new digital customer experience (CX) capabilities that enable any organization to quickly and easily deliver high-quality, omnichannel experiences that compete with the CX leaders and drive high user adoption.
“OutSystems is on a mission to eradicate ugly apps,” said Paulo Rosado, CEO of OutSystems. “CX champions, like Uber and Amazon, have radically raised the bar when it comes to amazing user experiences – completely resetting customer expectations. Companies today, no matter their industry, have to match or exceed if they want to survive. With these new CX capabilities, OutSystems has leveled the playing field, making it extremely easy for any company to build great apps that rival the CX leaders, using the skills of their existing teams.”
The new OutSystems features help organizations accelerate their end-to-end customer experience transformation and deliver highly personalized omnichannel digital customer experiences up to 10 times faster than traditional development and without the constraints of “off-the-shelf” software packages.
OutSystems helps organizations deliver high-quality, highly personalized omnichannel customer experiences with the following new CX capabilities:
- Experience Builder for native-feel mobile applications: The new Experience Builder abstracts away the complexities of assembling the multiple pieces of the interfaces that make for an engaging, pixel-perfect mobile experience, allowing developers to focus on what matters most: delivering great user experiences. An easy-to-use web interface, coupled with development accelerators, such as fully customizable application flows and screen templates with built-in native behaviors, ensures teams can deliver experiences faster with the quality standards customers expect.
- Reactive web technology built-in, for high-performing, rich, client-side development: Deliver engaging experiences that are consistent across mobile and web, with rich, interactive interfaces and a modern technology stack. Interfaces are easily assembled using state-of-the-art UI building blocks that are reusable across channels, reflect CX best practices, and result in increased delivery speed and experience quality. A single language and codebase means existing developers can be more productive and the business can meet their needs at a faster pace and lower cost.
- Progressive Web Application (PWA) support for increased customer adoption and retention rates: Engage customers and employees through a new channel - easily discoverable applications that don’t need to be deployed and downloaded through the app stores, reducing obstacles to adoption. These apps are automatically packaged by the OutSystems platform and deliver high-performing, native-like experiences that take advantage of device integration, and work offline – all using the same codebase as their browser or native counterparts, and without compromising on experience quality.
- Conversational experiences everywhere: Meet customers in the chat and voice platforms they interact with most. Whether using Whatsapp and Facebook Messenger for chat, or Siri, Google Assistant, Alexa, and Cortana for voice, by providing development teams with building blocks and a framework to create the most common chatbot and voice interaction patterns, OutSystems removes the complexity and uncertainty of building these kinds of interfaces. Businesses can easily adopt, experiment, and scale first-line of support automation, internal support bots, and other conversational use cases, faster and without needing specialized AI developers.
The Latest
In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...
In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...
Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...
In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ...
Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...
Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...
Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...
The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...
The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...
In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...