Building Blox.ai

AI Beyond The Buzzword: How We Built Our Customizable, No-Code Data Organization Tool3 min read

March 1, 2022 3 min read

Customer Engagement Manager, Blox.ai

AI Beyond The Buzzword: How We Built Our Customizable, No-Code Data Organization Tool3 min read

Reading Time: 3 minutes

The need for a data organization tool

In 2022, companies are expected to have an average of 35 AI projects in place. While businesses turn to AI to secure a competitive edge over the others, there are challenges that stand in the way of them. These are embedded deep within multiple layers — at the root of which lies the ugly data problem.

Most organizations today aggregate data from multiple sources and channels. According to a recent survey, companies on average source data from over 400 different sources. What’s more, over 20% of organizations draw data from a whopping 1000+ sources. Data coming in from each one of these sources is often siloed. It could also be structured in a manner that is inconsistent and incompatible with the organization’s data organization structure. In fact, over 90% of the world’s data is unstructured and inaccessible for business operations.

In order to combat this, teams spend a substantial amount of time manually verifying, sorting, cleaning, and organizing the data.

Considering the sheer scale of volumes, this process is resource extensive and typically results in three critical issues:

  • Inefficient processes
  • Errors and inaccuracies in results
  • Substantial time and effort are required for quality checks

Off-the-shelf AI and automation tools are usually introduced to improve the efficiency of the process. However, these tools bring in a new host of problems — ML models are only as good as the data they are trained on. This means that teams require in-house ML engineers to work alongside domain experts to ensure the quality of the data going into the systems.

Furthermore, in order to ensure optimal knowledge sharing, a common language then needs to be engineered. This needs to be done for every domain introduced so that both parties can understand the process. 

Introducing: xBlox

In order to help businesses effectively organize and manage their data, we built xBlox. xBlox is a fully customizable, no-code, AI-powered data organization tool.

With xBlox, business teams can orchestrate the entire journey — from consolidating and transforming raw data to deploying custom AI models — all on a single interface. 

Teams can upload their data catalogs and label only ~10% of their total data points on an interactive, intuitive UI. During this, the system observes, learns from user interactions, and predicts labels for the remaining data points. Thus, organizing the data into a structure that is compatible with your internal systems.

As a result, raw data in the form of images, numerical, structured text attributes, and unstructured text are enriched with rich attributes. Then, the data is organized into a hierarchy that brings structure to your data management system. So that your teams can use it to build AI models that solve mission-critical problems. 

xBlox abstracts the underlying complexity of your data so that anyone can build ML models. Whether you’re a data labeler looking to tag training data, or an ML engineer looking to tune model hyperparameters, xBlox has got you covered. The easy-to-use interface allows teams without any knowledge of code to take part in creating models most relevant to their KPIs.

With xBlox, organizations can drastically reduce the amount of time and the resources needed to manage their data. They can focus on solving challenges that are critical to their KPIs. 

Teams can deploy their AI models in hours rather than months. And realize the value of their AI implementation in weeks!

Here’s the impact organizations have seen after integrating xBlox into their processes:

AI Beyond The Buzzword: How We Built Our Customizable, No-Code Data Organization Tool

We’re eager to put this self-learning chisel in your hands to help you derive unlimited value from your data. Whether it’s to answer insightful questions specific to your use case or act as a launchpad to build sense-making applications — the possibilities are endless.