Enhancing care quality through data-driven insights and AI integration
Customer overview
Pegasus is a specialist care provider supporting adults with complex needs across a network of residential care homes. Its in-house care documentation app, Bloom, helps staff record daily care activity and gives managers the information they need to plan and monitor high-quality care.
At a glance:
- Large volumes of care data captured daily across multiple homes
- Managers rely on Bloom to create reports, update care plans and monitor trends
- Strong appetite to improve data quality and explore safe, practical use of AI
The challenge
Pegasus wanted to strengthen the way data was captured, understood and used across Bloom. Care managers reported fragmented data, inconsistent reporting and a heavy administrative load. Pegasus also wanted to understand where AI could responsibly support future analysis, forecasting and care planning.
Key challenges included:
- Inconsistent, incomplete or free-text data reducing accuracy and comparability
- Managers spending majority of their time manually creating reports or other admin
- Lots of “detective work” required to find and cross-reference information across screens
- Limited ability to forecast trends or make data-driven decisions
- The ambition to integrate AI, but a need for guidance on how to do it safely, ethically and effectively
The client says…
“A huge thank you to the Zaizi team for the depth and quality of the discovery work. It was clear how much thought, care and engineering expertise went into it. Your genuine passion for the healthcare sector and understanding that goes beyond pure tech made a real difference to the work you delivered..”
Mark Busra, CEO Pegasus
Our solution and process
Zaizi brought together specialists in AI readiness, user research, data analysis, interaction design and technical architecture to assess Bloom’s current capabilities and shape a clear roadmap for improvement.
We spoke with end users, analysed real anonymised datasets, tested statistical models and designed high-fidelity dashboards to show what better could look like.
What we delivered:
- AI readiness assessment covering governance, data quality and organisational capability
- One-to-one user research with care home managers to understand real user needs
- Analysis of Bloom datasets and early proof-of-concept statistical modelling
- Figma prototypes including dashboards, alerts, forecasting tools and improved data capture
- Recommendations for AI governance, upskilling, data validation and future integration
- Technical architecture options and example source code to demonstrate feasibility
The results
- Improved data foundations – Clear recommendations to strengthen validation, categorisation and mandatory fields, enabling higher-quality datasets for reporting and AI.
- Insightful presentation approaches – Showing how existing data could be harnessed in a way that meets the needs of care home managers and improves patient care
- Practical AI roadmap – Early modelling demonstrated the feasibility of automated report generation and predictive insight for incidents, behaviour and care planning.
The benefits
1. Higher-quality, consistent care data
Clearer data structures and improved capture methods will mean staff record information more accurately, giving managers a reliable picture of daily activity and long-term trends.
2. Reduced administrative burden
Automated report generation and better-organised data could significantly cut time spent doing admin, freeing managers to focus more on people, not paperwork.
3. Faster, clearer insight for decision-making
New dashboards and visualisation concepts consolidate information in one place, helping managers spot issues sooner, identify patterns and act with confidence.
4. Safe, future-ready AI integration
A structured roadmap gives Pegasus clarity on how to use AI ethically and effectively, from forecasting to generating care-plan narratives without compromising safety or trust.
Read: How our user-centred approach won the trust of frontline officers at the borders
Next steps
Want to unlock better insight, faster reporting and a clearer path to responsible AI?
Speak to our team about running a discovery or Transformation Day to get started.
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