oolo AI
Growth Insights and Precise Decision Alerts
Company Overview
Snapshot
Founded in January 2020 by Yuval Brener and Roey Yaniv, oolo AI operates with 1–10 employees. The company raised $6 million across one funding round from 3 investors. In December 2023, oolo AI was acquired by AppsFlyer.
Business overview
oolo AI develops a digital platform that leverages machine learning to identify and analyze unusual data patterns, translating them into actionable business opportunities. The system focuses on recognizing significant changes and trends in data related to growth and revenue generation, providing users with alerts to facilitate informed decision-making. oolo AI serves markets within the Business Software sector, specifically targeting areas like Sales & Marketing Solutions, Advertising Platforms, and Data Analysis & Decision Support.
Strategic signal
In December 2023, oolo AI was acquired by AppsFlyer, marking a significant exit for the company. This acquisition indicates a strategic move by AppsFlyer to integrate oolo AI's capabilities, particularly its AI-powered user acquisition and monetization platform, into its offerings. For investors, this signals the validation of oolo AI's technology and its potential to enhance mobile app analytics and ad monetization strategies within a larger corporate structure.
Log in to access full profile ›Company Intelligence Q&A
- What was the most significant corporate event for oolo AI?
- In December 2023, oolo AI was acquired by AppsFlyer. This acquisition led to oolo AI ceasing its independent operations.
- When was oolo AI founded and by whom?
- oolo AI was founded in January 2020 by co-founders Yuval Brener and Roey Yaniv.
- How much capital did oolo AI raise?
- oolo AI raised a total of $6 million in March 2020, with investments from S Capital VC and 2B.VC.
- Which investors participated in oolo AI's funding round?
- In March 2020, oolo AI secured funding from investors including S Capital VC and 2B.VC.
- What is oolo AI's core technology?
- oolo AI's core technology involves using machine learning and artificial intelligence to detect anomalies and identify data patterns, particularly for optimizing ad monetization and user acquisition in mobile applications.