Jared Zhao was originally interested in the analysis of the data during his period at the UC Berkeley because he was attracted to how the raw data could turn into a story. Zhao founded his first data analysis startup Polyness in 2021. But the progress in generative artificial intelligence only a year later made Zhao understand what the politures was building was too complicated for what users would look for in a world Post-ketgpt and decided to change course.
The result was Athenic AI, a company that uses to perform data analysis for companies in all their data sources. Zhao, the founder and CEO, said that Athenic products are designed to be a central nervous system of the databases of an organization that can be used by anyone in the company, regardless of their experience of coding or data.
Zhao (pictured above in the center) added that Athenic is built to be flexible and can work with companies to get his Ai to understand the “tribal knowledge” of the company, KPI or internal terminology so that the IA has the context necessary to perform adequate analyzes.
Each Data Report The AI -based system includes an explanation of how IA has interpreted the data that make it easier for users to identify potential errors and provide the Feedback of the AI model. Zhao added that this helps with visibility and that while they want the IA to approach 100%precision, human data analysts cannot even reach 100%precision.
“Even when the system is wrong, it is aware that it could be wrong and explains to the user why he thinks he can be wrong,” said Zhao. “And that’s what a good data analyst does. They don’t only give you the relationship or the graphic designer, they also give you an executive summary that explains how you should interpret this and what they did to do this analysis. “
The company was founded in 2022 and launched its product in the summer of 2022. Since it was launched, Athenic has been able to land customers ranging from small startups to large companies including ADITEL and PMC. Zhao said that the company found many of its smaller customers through outgoing sales leads, but that most of their business customers came from incoming interest.
Athenic, based in San Francisco, now announces a 4.3 million dollar seed round led by the BMW I Ventures with the participation of Tenvc, Scrum Ventures and Stage 2 Capital, among others. Zhao said the money will be put to take and develop new technological skills.
“Today, the user asks questions and bring out the intuitions from the system they want to see,” said Zhao. “There is also a world in which data have a sort of innate intuition for the data that we would like to suggest to the user even before asking.”
Samantha Huang, Dean of the BMW I Ventures, told Techcrunch that he was introduced to Athenica in a kind of random way. Huang said his company decided to have a better feeling of the IA startup ecosystem in general and “boiled the ocean” reaching as many artificial intelligence startups as possible to obtain control of the atmosphere .
ATTENIC was one of these. Huang said that the company has distinguished itself from other data analysis companies due to the fact that it helps companies to obtain artificial intelligence models with the specific context and knowledge of the company.
“Many companies will use these generic, monetized and fundamental models, but the problem is, technically, the model, it is a bit stupid if you don’t know how the data in the customer’s environment are,” he said. “Jared has adopted a new approach, combining a graphic designer more fundamental models that have allowed him to fill that problem.”
The analysis data market is crowded and will probably get more and more, when the generative IA improves and more companies try to capitalize how the IA can improve the management and use of their data. Databrks is only an example in this sector that has collected over 19 billion dollars in risk capital and is currently evaluated at $ 62 billion. There are also numerous companies focused on the data archive and on the optimization that could easily expand in that space.
Zhao thinks that the approach of companies to focus heavily on the user’s experience and ensure that the models to the adequate corporate context helps them distinguish them.
“We just think that there are too many companies that are managed without the right knowledge, even if all the data are technically there,” said Zhao. “People at the top sometimes, not out of ignorance, many times they fly blindly, and this is the problem we really want to solve.”
