- MachEye — a natural search and AI-powered analytics leader — announced it has unveiled its enterprise business intelligence (BI) SaaS platform and it raised $4.6 million in funding
MachEye — a natural search and AI-powered analytics leader — announced it has unveiled its enterprise business intelligence (BI) SaaS platform built to enable all users within an organization to explore data and find intelligence. And combining natural search and AI-powered recommendations and interactive audio-visuals, MachEye offers a complete analytics platform to replace a staid market of tools limited largely to data analysts and IT. The company also announced it raised $4.6 million in seed funding led by Canaan Partners and with participation from WestWave Capital.
Compared to other traditional BI solutions — which require expensive implementations and rely on rigorous training to properly use —MachEye has drastically simplified the user experience in order to increase the speed, quality and ubiquity of data-driven decisions. And seamlessly integrating NLP and NLG, MachEye orchestrates AI in a completely automated and click-less way to produce data stories as “interactive audio-visuals” instantly. The power of MachEye — often compared to Google and YouTube in terms of its approachability, simplicity and personalized experience — is designed to grow users’ autonomy and increase use of data for smarter decision-making across companies.
Customers across retail, technology and education already use MachEye to reduce customer churn, identify growth opportunities, and increase forecasting accuracy. And Thinkster, an AI-driven tutoring and test prep program for K-12, has utilized MachEye to enhance its virtual learning initiatives, enabling tutors to ask questions about student performance and receive specific, personalized recommendations on how to improve student engagement and test scores.
Built as a “low-prep, no-prep” solution, MachEye connects to all data sources with no duplication or additional infrastructure. And MachEye already provides native connectors to cloud warehouses like Amazon Redshift, Microsoft Synapse, BigQuery, and Snowflake CDP as well as traditional warehouses including Oracle and SQL Server.
And MachEye is founded by Ramesh Panuganty, a four-time founder/CEO whose last company was acquired in 2017 by Splunk. He brings more than 15 years of experience building large AI and NLG systems and also holds 15 patents spanning various machine-learning, analytics and natural-search technologies.
“MachEye aims to completely democratize BI use, simplifying it to the point where anyone within any organization can get actionable insights from enterprise data in less than half a second. Put another way, it enables business users to talk to the data, and the data actually talks back.”
— Joydeep Bhattacharyya, general partner at Canaan Partners and MachEye board member
“MachEye is the only BI solution that can handle the unique challenges of our business. We are getting more demand than ever to fill the gaps created by new learning challenges. To make our tutors successful, only MachEye provides a hyper-personalized platform that analyzes millions of data points, with a very simple, consumable format. It enables faster decisions with natural search and greater engagement using audio-visuals. MachEye is truly a unique product.”
— Raj Valli, Founder and CEO of Thinkster
“Existing technologies have made strides in usability but still failed to empower all users to easily explore data and make decisions quickly. These solutions are complex to use and have resulted in a paradigm of ‘what you ask is what you get.’ The net result is that businesses lose trillions of dollars because the right decision is not being made on time or not being made at all. MachEye empowers entire organizations to make smarter decisions at scale, which we believe will lead to happier customers, more efficient operations, and, eventually, more valuable companies.”
— MachEye Founder and CEO Ramesh Panuganty
“What MachEye does is enable users to control the information they want to consume and remove the barriers to data consumption created by legacy services. This allows a more direct approach to timely data intelligence, and every user gets their own personal business companion. I like that.”
— Rob Enderle, principal analyst, Enderle Group