We've helped teams across the globe shape different data products, from engineering-driven solutions designed for data scientists, ML experts, and data engineers, to no-code and intuitive applications for business users.
User feedback of our software has changed from "this looks complicated" to
"this looks easy"
, and our software progressed from a prototype, to actual, real, usable software.
Explore our case studies below.
Just like how Webflow made web development easier without coding, Datawisp did the same for data analytics. To move forward, the company needed an MVP that not only worked well but also looked great. They were searching for product designers with experience in designing data-heavy apps, and Eleken was a perfect fit.
Reform allows you to access data from any API and quickly convert it into analytics-ready tables without the need for coding. While Precog’s engineers had developed the necessary code, they needed assistance with design.
Cylynx fights financial fraud in the finance industry using graph AI-based transaction risk monitoring. They approached Eleken to upgrade their demo into a full-fledged MVP, making their app accessible to individual users and corporations alike.
Do Russia-Ukraine relations offer any insights into China and Taiwan? This is the question the product we helped design aimed to answer. Our job was to create an interface showcasing Diplomatic, Informational, Military, and Economic (DIME) interactions between two countries.
Like any other SaaS product, a data product should focus on solving the problem of the end user, not just the data output user. While we’re not data scientists, our UX team delves into the issue to grasp technical user behavior. We collaborate closely with the client’s team to tackle complexities together.
We use a product mindset to design data products. Our design approach varies based on the type of product we are working on. We take into account the unique user needs and adapt our design process accordingly. When designing different types of products, we cater to different user groups.
Raw data, derived data, and algorithms primarily attract technical users, while decision support and automated decision-making products have a more diverse user base, including both technical and non-technical users.
Our clients' teams handle design decisions regarding data collection, derivation of new data, and API design, while we focus on selecting the data to be displayed and determining the optimal way to present it.
We take on the heavy lifting for your users, diligently curating and presenting only the most relevant information in a user-friendly format.
Replacing code with visual blocks is a great way to simplify the user interface and make it accessible even for non-technical users.
Web elements like tables, forms, or CRM-like user flows can streamline the process of working with data for the whole team.
“The approach to assign one main designer to our project, that worked full-time on it, was very unique, but it allowed them to build a very detailed understanding of our - sometimes a bit complex - product.”
"Eleken is very fast and efficient. Whenever we ask them for something, they have it ready by the next day. If we can’t provide immediate feedback, they keep working on other things to avoid wasting time waiting."
“The workflow with the Eleken team is seamless. They work as an embedded member of our team.”
Try working with us for three days at no cost.