Databox App Case Study: UI/UX Design and Development

System Deploys Your Data

Databox builds scalable data pipeline infrastructure & deploy machine learning and artificial intelligence models.

Introduction

Overview

Databox is a provider of consulting services and expertise for building and implementing large scale distributed reactive backend systems for processing massive large scale datasets.

Project Goal

Follow a battle-tested methodology, baked by years of experience, to build effective solutions and apply the tools to solve the real AL & ML challenges across a variety of different industries.

Problem

The challenge of doing it at scale becomes enormous without the power of ML techniques to understand each customer uniquely for their preferences, historical buying trends. Building the infrastructure to handle datafrom scratch.

Solution

Data pipelines enable large scale AI & ML modeling for data scientists and data engineers in an organization, helping to cut down the time needed to produce a model, and therefore increasing overall data strategy ROI.

Hollistic approach

How We Start

We defined necessary phases of the design process to get an understanding of a product and set an MVP definition. And, finally, come up with such solutions which will help to understand product-market fit and start getting real customer's insights.

Application Guide

User Flow

The user flow takes you from the entry point through a set of steps towards a successful outcome and final action of the product.

Application Guide

Wireframes

Based on the business’s and end-user’s requirements, we built and tested the huge numbers of scenarios to find a proper and easy way to add/schedule/experiment with data pipelines.

Style Guide

Guidelines

UI Design

Visual Design

UI Design

Dark Design

For the last few years the dark UI becomes really popular among clients. Dark theme feels modern, smooth and “techy”. Now, a lot of people prefer dark more often than light one.