Eilla AI raises $1.5 million to improve financial efficiency in private markets

You only have a minute? Here are 3 key takeaways from the article:

Bulgarian startup Eilla AI secured $1.5 million in seed funding from lead investor Eleven Ventures and joined by Fuel Ventures.

• The platform automates mundane tasks related to financial research, analysis and document creation by emulating industry professionals.

• With a growing user base from over 50 M&A banks and venture capital and private equity funds, the company plans to use the funding to expand its team and expand its offerings.

The story of Eilla AI begins in a perhaps unlikely place, in the Bulgarian town of Veliko Tarnovo, where all of its founders – Nikola Lazarov (CEO), Petar Petrov (CCO), Nikolay Babulkov (CTO) – grew up together . Later, two more founders from the same city joined the team: Filip Siderov as a software architect and Nikolay Papazov as a financial director. All with some commercial or technical experience in the financial world.

“We sat next to each other (with Petar) for five years and studied computer science and mathematics at the Vasil Drumev High School of Natural Sciences and Mathematics in Veliko Tarnovo. Needless to say, we are very good friends. After high school, we both majored in artificial intelligence and always discussed industry trends,” Lazarov told The Recursive.

Today, Nikola, Petar and Nikolay live together in London, from where they operate Eilla AI and find solutions to the many old and new problems raised by the financial industry. The startup also has a presence in Sofia, with two of its members based there.

Get rid of tedious tasks

Most of these problems are often related to tedious tasks that young professionals in financial companies have to perform. Eilla AI solves these problems by efficiently analyzing crucial data and generating comprehensive reports.

“The biggest problem we see in the industry is that a lot of energy and time is spent on repetitive and mundane tasks that can easily be automated, especially at junior level. Instead of manually collecting and analyzing information for hours, mapping a market could be done in seconds. Additionally, the industry is slow to adapt to new technologies and there are not many solutions suitable for M&A, venture capital and private equity,” says Lazarov.

In addition to using generative AI to mirror industry professionals and automate processes, the The platform also opens new perspectives and supports complex decision-making through the aggregation and analysis of large amounts of information in much less time than currently possible.

Eilla AI’s potential was therefore quickly recognized by investors such as Eleven Ventures, who recognized its talented team with unique expertise in deep domain knowledge of AI and M&A.

“The daily work of M&A, venture capital and private equity professionals has not evolved much over the past 30 years, dominated by lots of manual data retrieval and analysis, as well as the creation of ordinary documents. Eilla’s generative AI platform is a game-changer that will deliver superhuman productivity. What previously took hours and days will take just minutes, allowing people to focus on human interactions instead. Svetozar Georgiev, general partner of Eleven Ventures, said in a statement.

Expand the team and position yourself for growth

According to Lazarov, the company will use these new funds to further expand its team and further position itself in its target markets.

This funding will be vital as we aim to expand our technical team and product offering, while positioning the company for growth in the M&A, venture capital and private equity markets,” he said. -he declares.

The Bulgarian startup also plans new trends in AI it could revolutionize the way M&A, venture capital firms, and investment firms in general operate.

“We think that the The ability to quickly analyze the smallest details of a single company while researching thousands of companies in minutes would enable a much more systematic and consistent way of advising and investing. Other examples would be researching a company and its competitors for creating a company profile or analyzing the fund portfolio. In the future, we plan to support more complex tasks such as building financial models, analyzing customer KPIs, etc. concludes Lazarov.

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