Case Studies
Care
Statement
Report
Client: Mirus Australia
CONTEXT
Mirus Australia is a trusted consulting and software solution provider for aged care organisations across Australia. Their solutions include Care Statement Reports designed to monitor and communicate the life and care of residents in aged care homes. These reports give an overview of residents' overall well-being — their activities, health and therapy status, nutrition, mood, and more — and are sent to both residents and their families monthly.
PROBLEM
The Care Statement report consists of eight pages / sections, 22 sub sections and a total of 33 data points from four different systems. Usually, age care centres have between 20 to a thousand beds, and this report needs to be done for each resident every month. It takes about 1-2 hours to complete each report. Due to the work being highly manual, every month a lot of working hours is spent by senior care staff which is costly and a poor use of their time.
SOLUTION
The project aimed to automate Care Statement report generation by combining Python-driven ETL pipelines with AI-powered narrative generation, boosting efficiency and cutting operational overhead. To achieve this, we built a lean ETL flow in Python for data ingestion and transformation, then leveraged AWS serverless services for hands-off scaling.
We used AWS Lambda for all compute tasks, AWS Step Functions to orchestrate each ETL step, Amazon S3 to stage raw and intermediate data, and Amazon RDS for relational storage. This combination met the client's goal of minimizing both infrastructure footprint and ongoing maintenance.
At the heart of the automation, we integrated AWS Bedrock's LLM endpoints into our Python scripts to generate human-readable report summaries and answer ad-hoc queries—complete with built-in retries and prompt-caching to control latency and costs. We also employed advanced prompt-engineering workflows (for example, prompt-chaining) to extract structure from unstructured data and maximize the LLM's accuracy and consistency.
Despite a tight timeline and holiday season challenges, our experienced team kept the project on track. The team's proactive and pragmatic stance helped manage the project's complexities effectively. A lot of positive energy, as well as a good sense of humor, definitely helped.
RESULTS
Mirus Australia demonstrated the report to their clients and has received overwhelmingly positive feedback. We made an MVP. It works, concept proven. Roll out planning for four sites is almost complete!
Next step, LAUNCH!
AI-powered
Compliance
Client: Letzz
CONTEXT
In highly regulated industries such as iGaming, keeping up with compliance can be time consuming and costly. Resource constraints often force compliance teams to be reactive, focusing on keeping the business compliant instead of being its partners, actively involved in company strategy and sustainable growth. The available tools fail to provide significant assistance.
PROBLEM
Overwhelming changes, increasing costs with smaller or static budgets, jurisdictional knowledge gaps, the lack of efficient tools and constant firefighting - it is all straining scarce and costly resources, making teams struggle to balance compliance and growth and keeping the potential strategic value of compliance unutilised.
At the same time, there is understandable skepticism about the use of automation in compliance. The key issue with using artificial intelligence in the field of law and legislation is the level of accuracy, which must be very high.
SOLUTION
We developed a technical solution for Letzz, the first AI-powered compliance workspace. Letzz turns regulatory updates into validated, actionable, and audit-ready tasks, helping teams implement changes faster, cheaper, and with less risk.
The platform continuously monitors and validates official regulatory updates, automatically turning them into mapped requirements and action-ready tasks that compliance and product teams can directly implement. Each task comes with full traceability and audit-ready evidence, giving teams confidence that every change is properly interpreted, documented, and provable.
With Letzz, operators move from manual, fragmented, and reactive compliance toward a proactive, data-driven, and collaborative model. The result is faster market entries, reduced dependency on external consultants, and fewer audit headaches — all within a secure, easy-to-use workspace that connects compliance with the rest of the business.
Letzz features industry-leading encryption, strict compliance with all major data protection regulations, user-friendly design and secure, customisable environments.
Tech Stack: Java, PostgreSQL, Spring Boot, Python, React, TypeScript, Docker, Kubernetes.
RESULTS
In its MVP phase, Letzz saves up to 25% of the time operators spend on researching regulations and understanding changes. Currently, the product is tailored to the iGaming industry in several European markets, where compliance is a complex challenge that requires significant resources.
Letzz raised the first investment from Henrik Tjärnström, the former CEO of Kindred Group (now part of FDJ UNITED), one of the globally leading iGaming operators.
HAIP
Client: HOOLOOVOO
CONTEXT
After the AI breakthroughs of 2022, as a tech company working for clients with complex platforms and huge datasets, we decided to focus on AI. The idea was to build our expertise and use AI to improve our own operations, as well as to be able to develop our own AI products and help our clients use the technology's advantages.
PROBLEM
Most of our engineers did not have any real experience with AI. Our non-tech people had little or no understanding of AI's concepts and capabilities. At least some of them were skeptical towards AI models, and most lacked understanding of how AI can assist them in their everyday work and life. To be able to achieve expertise and even sell it to our clients, we wanted to embrace an AI-Forward approach in our everyday business, as part of the culture across all departments within our company.
SOLUTION
Our engineers developed HAIP (HOOLOOVOO AI Playground), a platform featuring several custom AI assistants, as an easy to use internal tool for introducing and using AI across our organisation.
HAIP's AI assistants are highly adaptable - using 10+ integrated AI models, they are designed to select the ones best suited for each task and leverage their advantages. As additional AI-powered tools, the assistants offer advanced chat options, such as document upload, summarization, translation and search, etc.
Providing robust encryption, with user data not used for training of AI models, HAIP is a safe, secure and user-friendly AI resource, tailored to the unique needs of different departments and teams.
How did we do it under the hood? We integrated HAIP with our Java-based library to streamline interactions with various AI providers such as OpenAI, Anthropic, Amazon Bedrock, and simplifying AI integration across applications. Our backend relies on Java, PostgreSQL, and Spring Boot for efficient service development, including secure user authentication and authorization through a custom IAM component. For the frontend, we use React with MaterialUI to ensure consistent, responsive, and user-friendly design. Docker and Kubernetes manage backend infrastructure, providing stable, scalable, and efficient application deployment and resource utilization.
AI is rapidly evolving, and HAIP is continuously evolving too — with constant improvements that address our users' business needs in increasingly efficient ways.
Tech Stack: Java, PostgreSQL, Spring Boot, React, TypeScript, Docker, Kubernetes.
RESULTS
HAIP provided a perfect gateway for democracy in AI tools and helped our people (all our people) understand, adopt and use AI. Over 60% of our people (and growing) now habitually use AI in their daily work and feel good and safe about it.
After more than a year of practical use and constant improvements, HAIP is now used by a number of other organizations. The experience of our clients is now helping us develop new advanced AI-powered assistants and tools.