AI is changing how software is built, but not what makes for good software.
At Smartshore, we use AI where it truly adds value: to move faster from idea to prototype, to streamline our development process, and as the foundation for AI-powered applications. At the same time, we ensure that everything we deliver is secure, manageable, and ready for production.
Within our development teams, we work with ADA, our in-house AI assistant that actively participates in the development process. ADA analyzes code, identifies inconsistencies, suggests improvements, and streamlines tasks that would otherwise involve a lot of repetitive work. In addition, we use AI tools to quickly generate working prototypes before we begin building in earnest. This allows us to validate assumptions early on, save time, and avoid spending weeks working in a direction that doesn’t work.
We build applications where AI is at the core of the functionality. One example is the Noise Pollution Management application, which uses AI to analyze complex data and translate it into actionable insights for end users. We design such applications from the ground up: from model selection and data ingestion to interface and management. We always pay close attention to what needs to happen if an AI component produces an unexpected result.
Vibecoding makes it possible to build a working application in a short amount of time. However, a generated prototype is not the same as an application that is ready for real users. It typically lacks security layers, monitoring, scalable hosting, and structured code that is maintainable in the long term. Smartshore takes that step. We assess existing prototypes, determine what is usable and what needs to be rewritten, and bring the application up to production standards. That means: secure authentication, proper data storage, automated testing, CI/CD pipelines, and hosting on our own Kubernetes infrastructure in Amsterdam. After that, we keep it running.
AI applications are not static software. Models are updated, dependencies change, and vulnerabilities arise in unexpected places. Our AI DevOps offering ensures that AI-powered applications remain secure and stable even after going live. We actively monitor, identify vulnerabilities with CVSS scores as soon as they are known, and proactively implement updates. Clients choose their own level of involvement: notification with advice, or full implementation by our team. This applies to both the application layer and the AI components themselves.
Implementing AI isn’t just a matter of plugging in a model and waiting to see what happens. We follow processes that determine where AI is and isn’t involved, how the output is verified, and what happens if a model deviates from expectations.
Customer data and project data remain in Europe. Our infrastructure runs on DigitalOcean in the AMS region. We do not use AI tools that process training data without explicit consent. For each project, we specify which data AI tools are permitted to access and under what conditions.
Where AI output is directly visible to end users, we build validation layers. Model output is not passed on blindly. For each application, we define what constitutes acceptable behavior, what is flagged as an anomaly, and how that is logged and handled.
We monitor not only uptime and availability, but also the behavior of AI components in production. Drifting, unexpected output patterns, and latency issues are identified and documented.
We do not process personal data through external AI services unless there is an explicit legal basis and a data processing agreement in place. When designing AI functionality, we routinely ask whether a decision supported by AI should also be explainable and contestable. For applications in regulated sectors or those that impact individuals, we always address this explicitly.
Smartshore is ISO 27001 and ISO 9001 certified. This applies to our teams in Utrecht, Ludhiana, and Panaji. It’s not just a formality, but a practical framework for how we handle information and processes.
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