Product Design

App

AI

LORE

Helping farm managers track performance, diagnose issues and make faster decisions

Product Design

App

AI

LORE

Helping farm managers track performance, diagnose issues and make faster decisions

Product Design

App

AI

LORE

Helping farm managers track performance, diagnose issues and make faster decisions

Prodap, now dsm-firmenich, is a company in the agricultural sector that offers, among its products, digital solutions for large beef cattle farms in Brazil.

Project Summary

When I joined the project, the idea of an AI assistant for livestock management was still abstract. I led the design of LORE from the ground up—translating raw data problems into a tool that helped farm managers act faster and smarter. By aligning the assistant with existing systems like Views Master, I increased adoption, improved user workflows, and supported the company’s growth strategy.

Impacts

  • The first AI assistant for cattle farm managers.

  • 70 million Swedish kronor invested in the app over a two-year period.

  • dsm-firmenich acquired PRODAP.

Role

Product Designer

Team

1x Product Manager

1x Product Owner

3x Product Designers

6x Developers

Timeline

18 months

Problem


As a Product Designer at PRODAP, I engaged directly with farm managers who were using other PRODAP solutions. A key challenge they faced was interpreting the massive flow of daily data. My mission became clear: transform that raw, intimidating data into an intuitive and empowering tool. The goal was to provide them with faster, more accessible insights to streamline operations and drive decisive action.

Problem


As a Product Designer at PRODAP, I engaged directly with farm managers who were using other PRODAP solutions. A key challenge they faced was interpreting the massive flow of daily data. My mission became clear: transform that raw, intimidating data into an intuitive and empowering tool. The goal was to provide them with faster, more accessible insights to streamline operations and drive decisive action.

Problem


As a Product Designer at PRODAP, I engaged directly with farm managers who were using other PRODAP solutions. A key challenge they faced was interpreting the massive flow of daily data. My mission became clear: transform that raw, intimidating data into an intuitive and empowering tool. The goal was to provide them with faster, more accessible insights to streamline operations and drive decisive action.

Responsibilities

I needed to build a bridge between overwhelmed users and clarity. So, I led the design of LORE from concept to MVP:

  • Drove Design Sprint, UX research, ideation and user validation.

  • Designed conversation flows, wireframes, visuals and data tables.

  • Created visual style guide.

  • Facilitated collaboration between stakeholders (consultants, developers, PMs, client reps).

Led the design of LORE from concept to MVP:

  • Drove Design Sprint, UX research, ideation and user validation.

  • Designed conversation flows, wireframes, visuals and data tables.

  • Created visual style guide.

  • Facilitated collaboration between stakeholders (consultants, developers, PMs, client reps).

Led the design of LORE from concept to MVP:

  • Drove Design Sprint, UX research, ideation and user validation.

  • Designed conversation flows, wireframes, visuals and data tables.

  • Created visual style guide.

  • Facilitated collaboration between stakeholders (consultants, developers, PMs, client reps).

Research Process


I rallied the team around a Design Sprint. We defined personas, mapped workflows, and used value vs. effort matrix to prioritize features for a high-impact MVP.

I then sketched out conversation flows, wireframes, visuals, and data dashboards. Together with consultants, devs, PMs, client reps, we defined a visual language and structure that made sense to farmers in real-world contexts.

Research Process


I rallied the team around a Design Sprint. We defined personas, mapped workflows, and used value vs. effort matrix to prioritize features for a high-impact MVP.

I then sketched out conversation flows, wireframes, visuals, and data dashboards. Together with consultants, devs, PMs, client reps, we defined a visual language and structure that made sense to farmers in real-world contexts.

Insights

The research process led us to brainstorm several ideas, including:

  • A tool that generates data and also sets actions for each situation/problem.

  • Send notifications to get the user's attention and get them to log into the app to check what's the farm status.

  • Have a feature for Tasks Management on the farm.

  • Compliment employees on their performance.

  • News about the agricultural market.

The research process led us to brainstorm several ideas, including:

  • A tool that generates data and also sets actions for each situation/problem.

  • Send notifications to get the user's attention and get them to log into the app to check what's the farm status.

  • Have a feature for Tasks Management on the farm.

  • Compliment employees on their performance.

  • News about the agricultural market.

The research process led us to brainstorm several ideas, including:

  • A tool that generates data and also sets actions for each situation/problem.

  • Send notifications to get the user's attention and get them to log into the app to check what's the farm status.

  • Have a feature for Tasks Management on the farm.

  • Compliment employees on their performance.

  • News about the agricultural market.

Solution


Our solution is a AI-powered tool to automate and enhance what farm managers and owners need: data visualization and actionable insights. LORE processes large volumes of real-time data, identifies patterns and provides precise recommendations. Other features include:


  • Reports and graphs on animal feed consumption.

  • Performance results from each farm area.

  • Overall analysis of farm operations.

  • Quick messages (e.g., alerts, reminders).

Solution


Our solution is a AI-powered tool to automate and enhance what farm managers and owners need: data visualization and actionable insights. LORE processes large volumes of real-time data, identifies patterns and provides precise recommendations. Other features include:


  • Reports and graphs on animal feed consumption.

  • Performance results from each farm area.

  • Overall analysis of farm operations.

  • Quick messages (e.g., alerts, reminders).

Business Alignment

As part of the design strategy for LORE, we identified an opportunity to integrate data from Prodap Views Master, an existing monitoring system used by many of our clients. We achieved two key business outcomes:

  • Increased product synergy: LORE became a natural extension of Views Master, encouraging clients to adopt both solutions.

  • Accelerated sales cycle: The integration added immediate value for existing customers, reducing onboarding time and making the offering more attractive.

Business Alignment

As part of the design strategy for LORE, we identified an opportunity to integrate data from Prodap Views Master, an existing monitoring system used by many of our clients. We achieved two key business outcomes:

  • Increased product synergy: LORE became a natural extension of Views Master, encouraging clients to adopt both solutions.

  • Accelerated sales cycle: The integration added immediate value for existing customers, reducing onboarding time and making the offering more attractive.

Business Alignement

As part of the design strategy for LORE, we identified an opportunity to integrate data from Prodap Views Master, an existing monitoring system used by many of our clients. We achieved two key business outcomes:

  • Increased product synergy: LORE became a natural extension of Views Master, encouraging clients to adopt both solutions.

  • Accelerated sales cycle: The integration added immediate value for existing customers, reducing onboarding time and making the offering more attractive.

Pilot Clients and User Feedback

  • Conducted two rounds of client interviews: after 3 and 6 months of usage.

  • Initial stage involved 9 client organizations; later stage involved 16, segmented by engagement level.

  • Semi‑structured interviews assessed daily routines, data practices, mobile use, engagement with LORE and feedback for improvements.

  • Analysis helped shape feature updates and design language over time.

  • Conducted two rounds of client interviews: after 3 and 6 months of usage.

  • Initial stage involved 9 client organizations; later stage involved 16, segmented by engagement level.

  • Semi‑structured interviews assessed daily routines, data practices, mobile use, engagement with LORE and feedback for improvements.

  • Analysis helped shape feature updates and design language over time.

Lessons Learned

  • Writing clear, concise messages for an AI assistant is harder than it seems—especially for users in rural or low-tech contexts. After receiving feedback that 70% of users found the messages too long or confusing, I enrolled in a UX Writing course to sharpen my content design skills.

  • Working with farm specialists taught me how to ask better questions and adapt design language to different knowledge levels.

Lessons Learned

  • Writing clear, concise messages for an AI assistant is harder than it seems—especially for users in rural or low-tech contexts. After receiving feedback that 70% of users found the messages too long or confusing, I enrolled in a UX Writing course to sharpen my content design skills.

  • Working with farm specialists taught me how to ask better questions and adapt design language to different knowledge levels.

Results

Following the pilot testing, LORE was added to dsm-firmenich's portfolio of digital products, proving to be a success story - as demonstrated by this client testimonial in the video below (in Portuguese):

"It's a fantastic application that shows you exactly what is happening on the property, even when you're not there. Decisions are made quickly because I have the data in the palm of my hand to plan the best strategy and achieve the planned objectives," says Ricardo Cezar Espírito Santo, farm Bom Sucesso owner.

  • LORE became the first AI assistant for cattle farm managers in its category.

  • Over two years, it attracted 70 million SEK in investment.

  • dsm-firmenich (formerly Royal DSM’s acquisition of Prodap) added it to their product family.

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Contact

lucisprados@gmail.com

+46 73 860 5149

Connect on Linkedin

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Contact

lucisprados@gmail.com

+46 73 860 5149

Connect on Linkedin

Back to top

Contact

lucisprados@gmail.com

+46 73 860 5149

Connect on Linkedin

Back to top