Welcome to the Orbilon Technologies blog, your resource for expert insights on AI development, web and mobile application engineering, automation, DevOps, and SaaS best practices. Our team shares practical guides, industry analysis, and technical deep-dives to help developers, founders, and business leaders make smarter technology decisions.
Whether you are exploring AI agents, evaluating cloud infrastructure options, or looking for development best practices, our articles are written by engineers who build these solutions every day.
Why .NET + AI Is Perfect for Enterprise Applications becomes the Best Combination? Introduction Without a doubt, such companies require solutions that are not only smart but also able to size up rapidly do they. The synergy between .NET and AI is the main reason companies get the solution they
Why We Love Hero Animations in Flutter | Smooth App Transitions Guide Introduction Among the most charming features of Flutter are hero animations, which basically convert the usual screen changing into beautiful, captivating working methods. Such smooth transitions are a kind of app “life” which is very much appreciated by
How to Develop Real-Time AI Pipelines in Python: An Easy-to-Follow Plan Introduction Creating real-time AI pipelines is a must for any application that is trendy and needs to provide quick predictions and answers. It doesn’t matter if you are making recommendation engines, fraud detection systems, or the controls of an
Your Cloud Ops Are Ready to Be Automated Introduction Contemporary cloud platforms work at a velocity that is significantly beyond the capability of human intervention. This is why teams are almost daily confronted with difficulties in scaling, sudden degradation of performance, unexpected cost spikes, and unplanned outages. To these problems,
How Flutter Apps Are Becoming AI-Native Introduction Mobile apps are going into a different age where smartness is just as important as appearance. Flutter, which is famous for its quick UI, is actually moving towards being an AI-native framework, a single one that can facilitate smart features, on-device models, and
How n8n Replaces 7 SaaS Tools With One Automation Layer Introduction Businesses use many SaaS applications to manage sales, marketing, customer service (CRM), and other tasks. Managing too many different applications at once results in overusage, higher costs, and inefficient processes for many companies. N8N offers an affordable solution with
How to Speed Up Your .NET APIs by 50x: The Simple Caching Strategy Most Developers Overlook Introduction API performance is what determines whether your application’s user experience is fantastic or terrible. Complex optimization techniques, which developers frequently talk about, are in fact seldom the reason for performance improvement, but one
Agentic AI Replacing RPA: Why Smart Businesses Are Making the Switch Introduction For several years, Robotic Process Automation (RPA) was the tool that made businesses happy by its efficient handling of monotonous tasks. Nevertheless, a new paradigm is emerging: Agentic AI. The transition from RPA to this smart automation solution,
Using LLMs with APIs: A Complete Guide to Intelligent Automation Introduction It is no longer a secret that the use of APIs to integrate large language models has changed the way companies operate and make automated, intelligent decisions. If you are a developer creating conversational agents for customer support, writing
Unit Testing CQRS with Moq & MediatR Introduction CQRS (Command Query Responsibility Segregation) can be regarded as one of the best patterns when making clean and scalable .NET applications. Essentially, the pattern divides the read and write operations, thus developers can have less complex, more predictable, and easily maintainable logic.
AI Makes Zero-Trust Security Smarter Introduction Zero-Trust Security is a worldwide standard for the protection of information in technology of today. It zero-trust principle (never trust, always verify) is characterized by the fact that trust is not assumed for users, devices, or networks, but they are nevertheless verified. However, due
How AI Converts Marketing Data Into Automated Decisions Introduction Marketing teams today have a problem. They have tons of data but not enough time to look at it. Businesses track what customers do, sales numbers, how well campaigns perform, and what’s said on social media. But hardly any of them