Prectavi
Prectavi
From product data to live batch intelligence.
From product data to live batch intelligence.
Industry
Pharmaceutical
Role
Lead UI/UX Designer
Timeline
Jan 23 - Sept 25
Product type
B2B Saas
Industry
Pharmaceutical
Role
Lead UI/UX Designer
Timeline
Jan 23 - Sept 25
Product type
B2B Saas
THE CHALLENGE
THE CHALLENGE
Turning complex QA workflows into a scalable product
Turning complex QA workflows into a scalable product
Prectavi is an early version for a predictive QA platform founded by the life science department of Avato Systems to help pharmaceutical teams connect product setup, quality parameters, batch data, and live production monitoring in one structured workflow. The project was developed during a sales and pitching phase, where the goal was not only to shape a compelling product vision for stakeholders, but also to design clear user flows that could communicate the system’s value despite the complexity of the domain. The challenge was to create an entirely new, highly data-driven QA tool within a defined budget and scope, while translating deep pharmaceutical quality assurance processes into an interface that felt modern, intuitive, and scalable. Building on the Lifesize Design System also used across other pharma products such as NMVS Core, I worked with a UX conceptor from my team to redesign the experience from the ground up and turn a complex operational framework into a more universal and easy-to-use quality management tool.
Prectavi is an early version for a predictive QA platform founded by the life science department of Avato Systems to help pharmaceutical teams connect product setup, quality parameters, batch data, and live production monitoring in one structured workflow. The project was developed during a sales and pitching phase, where the goal was not only to shape a compelling product vision for stakeholders, but also to design clear user flows that could communicate the system’s value despite the complexity of the domain. The challenge was to create an entirely new, highly data-driven QA tool within a defined budget and scope, while translating deep pharmaceutical quality assurance processes into an interface that felt modern, intuitive, and scalable. Building on the Lifesize Design System also used across other pharma products such as NMVS Core, I worked with a UX conceptor from my team to redesign the experience from the ground up and turn a complex operational framework into a more universal and easy-to-use quality management tool.
Prectavi is an early version for a predictive QA platform founded by the life science department of Avato Systems to help pharmaceutical teams connect product setup, quality parameters, batch data, and live production monitoring in one structured workflow. The project was developed during a sales and pitching phase, where the goal was not only to shape a compelling product vision for stakeholders, but also to design clear user flows that could communicate the system’s value despite the complexity of the domain. The challenge was to create an entirely new, highly data-driven QA tool within a defined budget and scope, while translating deep pharmaceutical quality assurance processes into an interface that felt modern, intuitive, and scalable. Building on the Lifesize Design System also used across other pharma products such as NMVS Core, I worked with a UX conceptor from my team to redesign the experience from the ground up and turn a complex operational framework into a more universal and easy-to-use quality management tool.
APPROACH
APPROACH
Using design exploration to clarify a complex product vision
Using design exploration to clarify a complex product vision
The approach was first and foremost about setting priorities and clearly illustrating the idea in a way that showed a high degree of feasibility. In this phase, the main goal was to help explain the concept convincingly to inhouse stakeholders, the user group, and the internal decision-makers who would potentially become customers later on, since the project was still in a business-driven phase. That meant the work had to focus less on perfecting a final solution and more on communicating the principle clearly, using both low-fidelity and high-fidelity prototypes to explore the space, test directions, and make the concept tangible early on. Rather than chasing perfection too soon, the process stayed iterative, interactive, and exploratory, with room to refine the experience in later phases through testing and presentation. Engineering was only lightly involved at this stage, which made flexibility and collaborative exploration even more important.
The approach was first and foremost about setting priorities and clearly illustrating the idea in a way that showed a high degree of feasibility. In this phase, the main goal was to help explain the concept convincingly to inhouse stakeholders, the user group, and the internal decision-makers who would potentially become customers later on, since the project was still in a business-driven phase. That meant the work had to focus less on perfecting a final solution and more on communicating the principle clearly, using both low-fidelity and high-fidelity prototypes to explore the space, test directions, and make the concept tangible early on. Rather than chasing perfection too soon, the process stayed iterative, interactive, and exploratory, with room to refine the experience in later phases through testing and presentation. Engineering was only lightly involved at this stage, which made flexibility and collaborative exploration even more important.
EXPERIENCE DESIGN PROCESS
EXPERIENCE DESIGN PROCESS
Exploring interface patterns to shape a clear product direction
Exploring interface patterns to shape a clear product direction
Since the project started in a sales-driven context, the priority was to develop a convincing product direction that could communicate value early, rather than define a final-state solution too soon. A major part of that work was experimenting with different UI patterns and layout models — including widget-based dashboards, table views, card-based overviews, and other structural interface variations — to understand which formats could best organize complex pharmaceutical data and make the system feel easier to navigate. At the same time, the Life Science Design System was adapted on the color and spacing level to test a more modern and flexible visual language. This made it possible to explore how a highly complex QA platform could become more accessible, more visually engaging, and better suited for stakeholder presentations without losing its technical credibility.
Since the project started in a sales-driven context, the priority was to develop a convincing product direction that could communicate value early, rather than define a final-state solution too soon. A major part of that work was experimenting with different UI patterns and layout models — including widget-based dashboards, table views, card-based overviews, and other structural interface variations — to understand which formats could best organize complex pharmaceutical data and make the system feel easier to navigate. At the same time, the Life Science Design System was adapted on the color and spacing level to test a more modern and flexible visual language. This made it possible to explore how a highly complex QA platform could become more accessible, more visually engaging, and better suited for stakeholder presentations without losing its technical credibility.
SOLUTION
SOLUTION
High-fidelity user flows for complex QA scenarios
High-fidelity user flows for complex QA scenarios
The output was a set of high-design-quality user flows that made complex pharma QA processes more tangible, intuitive, and visually compelling across different devices and interface formats. By translating predictive QA, production monitoring, and batch-related workflows into clear and structured experiences, the concept helped illustrate multiple ways of addressing user pain points while keeping the system credible, realistic, and aligned with a feasible budget.
The output was a set of high-design-quality user flows that made complex pharma QA processes more tangible, intuitive, and visually compelling across different devices and interface formats. By translating predictive QA, production monitoring, and batch-related workflows into clear and structured experiences, the concept helped illustrate multiple ways of addressing user pain points while keeping the system credible, realistic, and aligned with a feasible budget.
REFLECTION
REFLECTION