Flink Labs works with organisations facing complex questions,
imperfect data, and decisions that matter.
Our client work sits alongside our research practice. We partner
closely, build carefully, and focus on systems that are
understandable, usable, and durable in real conditions.
Since 2014, we’ve worked with healthcare providers across Victoria, Queensland, and New Zealand, analysing more than 50 million patient experiences.
The focus has been on turning large volumes of unstructured feedback into insights clinicians and executives can actually use. The systems support early signal detection, trend analysis, and decision-making grounded in lived patient experience, not just metrics.
Working with investigative journalists, we built tools to surface coordinated networks spreading climate misinformation.
Rather than individual articles or actors, the system revealed patterns of behaviour across sources, helping journalists move faster from suspicion to evidence and focus their reporting where it mattered most.
For IBM, we designed an interactive platform for exploring complex global performance data.
The work focused on making large, multi-dimensional datasets legible through maps and visualisations that supported exploration, comparison, and strategic reasoning at a global scale.
We partnered with local governments to analyse tens of thousands of community comments each month.
The resulting systems combined machine learning with human oversight to surface emerging concerns, shifts in sentiment, and recurring themes. The emphasis was on clarity and trust, enabling councils to respond early and communicate more effectively with their communities.
For Australia’s Digital Transformation Agency, we led the design and delivery of an award-winning data visualisation platform.
The dashboard brought together complex performance data into a clear, shared view, supporting transparency and better decision-making across government.
We developed the VETStat analytics platform for the Victorian Department of Education to surface patterns across vocational education data.
The work helped policymakers understand participation, outcomes, and employer alignment, directly informing decisions aimed at improving student pathways and system performance.
Working with a major supermarket chain, we analysed in-store sensor data to understand how customers moved through physical space.
The insights informed store layout and design decisions, improving flow, engagement, and commercial outcomes without relying on invasive or brittle assumptions.
In collaboration with IP Australia, we built a prototype system to support patent and trademark examination.
The focus was on reducing manual load and improving consistency by helping examiners navigate large volumes of text and imagery more efficiently, without removing human judgement from the process.
If you want to explore what applied intelligence could look like in your context, let's talk.
