How Tellius Compares to WhizAI
for Self-Service Analytics

How Tellius Compares to WhizAI for Self-Service Analytics

WhizAI is a life science analytics platform that claims to leverage generative AI infused with domain expertise to derive insights. However, the platform is lacking enterprise-ready features like data preparation, dashboards, automated insights, and advanced analytics capabilities. These limitations mean WhizAI falls short on its promise to enable self-service analytics and insights, as organizations will run into issues scaling usage with a lack of enterprise-ready features.

Tellius offers true self-service analytics via a robust data preparation layer powered by generative AI, intuitive search, and industry-leading automated insights. From natural language search to automated insights and AutoML, Tellius upskills all user types with an augmented analytics experience.

Tellius vs WhizAI Overview

Self-service ad hoc data exploration and analysis Conversational data exploration with limited self-service analysis
Robust automated insight capabilities with a wide array of insight types, enabling you to understand “why” metrics are changing Automated insights limited to anomaly detection and key driver insights
Advanced analytics capabilities, including AutoML, no-/low-code model creation, and BYO model Limited predictive analytics experience with no AutoML nor no-code model creation
Intuitive, fast set-up, accelerated by world-class technology, people, and processes Initial set-up and implementation can stretch for months, with adoption failure a common occurrence
Robust data preparation layer, enabling you to combine data from multiple sources to augment the search experience Data preparation layer designed to enrich search experience and has limitations to transformations/joins

Why Tellius?

Designed from the ground up to provide an integrated experience that combines data preparation, transformation, querying, and insight generation, all in a user-friendly, intuitive platform

Empowers users to understand not only “what” is happening but also “why,” by running millions of variable combinations in the datasets, enhancing the depth and value of insights derived
Built with a powerful dual analytics engine that combines powerful ad hoc exploration capabilities for analytical queries at scale, optimized for data prep, insights, and ML workloads

Designed from the ground up to provide an integrated experience that combines data preparation, transformation, querying, and insight generation, all in a user-friendly, intuitive platform

Empowers users to understand not only “what” is happening but also “why,” by running millions of variable combinations in the datasets, enhancing the depth and value of insights derived

Built with a powerful dual analytics engine that combines powerful ad hoc exploration capabilities for analytical queries at scale, optimized for data prep, insights, and ML workloads

Detailed Feature Comparison

Feature

Tellius

WhizAI

Automated Insights

Yes
but limited

Kick-off Insight from Search

Key Driver Insights

…… Explore Top Segments

…… Explore Top Predictive Factors

Trend Insights

…… Explore Top Contributors to the Change

…… Explore Top Reasons for the Change

Comparison Insights

…… Explore Top Differences

…… Explore Top Reasons for the Difference

Data Preparation

Yes
but limited

Connect to the most popular enterprise data storage solutions

Data transformation capabilities

Automated synonym creation

Yes
with GenAI

Automated display name creation

Yes
with GenAI

Automated column description creation

Yes
with GenAI

Predictive Analytics

Yes
but limited

AutoML

Point-and-Click ML

Bring Your Own Model

Regression

Classification

Clustering

Recommender Systems

Anomaly Detection

Alerts

Feed to keep track of key metrics

Feed linked to automated insights

Yes
understand why metrics changed

Tellius

WhizAI

Common WhizAI Pitfalls

WhizAI’s automated insights experience is limited to key driver analysis. Having limitations on the types of analysis available means true self-service analytics is out of reach with WhizAI.

With a limited data preparation layer, enterprises struggle to leverage WhizAI at scale. Organizations must rely heavily on the WhizAI team to ensure natural language search functions correctly, and they have limited ability to address issues on their own.

Advanced analytics capabilities are limited with no AutoML or point-and-click model creation. These restrictions limit the ability for users to understand how best to proceed with next steps in decision-making.