Kiandra Insights
Modernising legacy systems: a smarter, safer path to reinvention
How AI, low-code, custom code and discovery-led delivery can transform 20-year-old systems without breaking the business
Many of Australia’s most critical business systems are 15, 20, even 30 years old. They’re built on technologies no longer supported, with business logic buried in code no one owns. Replacing them is risky, expensive and full of unknowns.
This guide explains how Kiandra uses modern techniques including low-code platforms, GenAI-assisted discovery, and custom-code redevelopment, to help organisations safely reimagine, rebuild and replatform these legacy systems. It’s designed for CIOs, CTOs and enterprise IT leaders ready to act but unsure where to start.
"We don’t fully understand our current system’s complexities." This is a common thing we hear. You’re not alone.
Most legacy systems evolved over years. Spreadsheets became apps. Quick fixes turned into core logic. Institutional knowledge was never documented. And now that knowledge lives in the minds of two people and one of whom just retired.
You can’t replace what you don’t understand. That’s why we start with visibility.
What you get with Kiandra
- A roadmap for replatforming based on fact, not guesswork
- A validated, co-designed prototype of ‘your most important workflows
- A plan for migration, training, and governance
- Full visibility into current-state system logic
- GenAI-supported analysis, mapping and documentation
- Custom or low-code redevelopment as required
- Partnership with a team that understands risk, compliance, and delivery.
Kiandra’s replatforming discovery process: Uncovering the unknowns
Legacy systems are often undocumented and opaque. Our Discovery Phase is designed to safely and efficiently reveal what’s really under the hood without disrupting business operations.
Step 1: Kickoff & context capture
- Stakeholder interviews: Understand the system’s history, business context, known pain points
- Business requirements mapping: Identify critical user journeys, dependencies, and interfaces
- Risk and priority assessment: Map areas of high regulatory impact or technical fragility.
Step 2: GenAI-assisted system analysis
- Source code ingestion: Use AI tools to parse legacy code (e.g. VB6, .NET, COBOL, Access, Oracle Forms)
- Progressive system decomposition: Breaks complex legacy systems into manageable parts for analysis, redesign, and incremental replacement or modernisation
- Logic extraction: Automatically document workflows, dependencies and business rules
- Visual flow mapping: Generate current-state flowcharts, data models, and object maps.
Step 3: Manual validation & expert review
- Manual validation: Ensure GenAI outputs are accurate and complete. This is where our engineering experience adds real value
- Cross-check AI outputs with SMEs (where available) to verify edge cases and business logic
- Gap identification: Flag undocumented behaviour, orphaned processes or abandoned integrations
- Prioritise components: Triage the system into “core”, “replaceable” and “retire”.
Step 4: Co-design the future state
- Design sessions with business users: Redefine what the system should do, not just what it does today
- Prototype candidate workflows: Use low-code or code-assisted tools to model future-state processes
- Rapid visual prototyping: GenAI allows rapid prototyping beyond workflows and can visualise future-state UI/UX to visualise potential improvements.
- Test usability, logic and performance: Test early with actual users, not just architects.
Step 5: Roadmap and risk planning
- Develop a modernisation roadmap: Phase-based plan for migration, rebuild, integration and rollout
- Estimate effort and risk based on fact, not guesswork
- Present recommendations on whether to refactor or rebuild in low-code, custom, or hybrid.
What makes this unique
- GenAI-powered analysis: Speeds up what normally takes weeks or months and makes the invisible visible
- Co-design, not guesswork: Aligns future-state design with current business priorities and real users
- Custom + Low-Code flexibility: We rebuild the right way for each function, not one-size-fits-all
- Security and governance baked in: We understand regulated environments, data privacy, and auditability.
If you'd like to learn more about modernising legacy systems, speak to the team today or book in your free proof of concept.
.svg){kind=icon}
More insights
The role of the Product Owner in successful software delivery
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.
If you want trustworthy AI, don’t start with the tech
“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.
Lovable app review: AI prototyping and product ideation tools for clients
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.
Let’s discuss your next project
Whether you’re curious about custom software or have a specific problem to solve – we’re here to answer your questions. Fill in the following form, and we’ll be in touch soon.
.svg)
