Insights & News

Your legacy systems are quietly costing you time, money, and opportunity. Learn why they are on borrowed time and how a modern, low-code approach can help you move forward with confidence.

Many organisations across Australia still depend on systems built decades ago. These platforms once did the job, but they now act as barriers to growth. They are costly to maintain, difficult to scale, and risky to secure. More importantly, they can no longer keep pace with the expectations of staff and customers.

Not long ago, many businesses only considered security after a breach occurred. Today, that approach is too risky. Security needs to be designed into software from the very beginning and treated as a non-negotiable part of the software development life cycle.

Not all projects succeed. In fact, research shows that around 70% of digital transformation initiatives fall short of expectations. The result? Wasted time, investment and resources. With more than $1 trillion being invested globally in digital transformation, this is an initiative you’ll want to get right.

At Kiandra, we work closely with Product Owners to bridge the gap between their organisation’s needs and our delivery team’s technical expertise. This collaboration is crucial for keeping the project aligned to business goals, managing scope effectively, and ensuring value is delivered.

“How do we make sure our AI systems behave responsibly, not just accurately?” We get this question a lot. Usually after something has already gone a bit sideways. Here is the short answer: You build responsibility into AI from the very beginning. Guided by our B-Corp principles, we see responsible AI as a balance of purpose and effectiveness.

When working with clients in the earliest stages of a project, speed matters. The faster we can turn ideas into something visual, the sooner we can test assumptions, get feedback, and align on a direction. That’s where product ideation tools like Lovable come in.

AI is reshaping how software is built, used and maintained but most organisations aren’t starting from scratch. They’re working with what they already have: legacy platforms, off-the-shelf SaaS, or custom tools that still perform core business functions.

When projects succeed, it’s rarely by accident. Clear, accurate requirements are the foundation of great software but they’re also the part most prone to misunderstanding. At Kiandra, we use AI prototyping and a multiple LLM workflow to make this step faster, more accurate, and more collaborative.

AI isn’t some futuristic toy we’re tinkering with on the side. It’s already woven into the way we get work done at Kiandra. Whether it's helping sift through mountains of invoices or modernising stubborn legacy code, we’re using AI to tackle the headaches that come with real-world software delivery.

Travel businesses need systems that do the work with faster quotes, smarter pricing, and better traveller experiences. We’ve mapped the common travel challenges in the industry, and exactly how AI can solve them.

In transport and logistics, most operators don’t need to be sold on the benefits of AI, they just need a clear path to making it work. This blog post outlines the most common challenges we see across logistics businesses, and how AI, when implemented correctly, can solve them and improve performance.