Proofpoint: The $12B Deal Behind an AI-Driven Cybersecurity Leader скачать в хорошем качестве

Proofpoint: The $12B Deal Behind an AI-Driven Cybersecurity Leader

Season 4 of Behind the Deal kicks off with a deep dive into Proofpoint, a key investment within Thoma Bravo’s cybersecurity portfolio. Seth Boro and Andrew Almeida reflect on the conviction behind the firm’s largest software buyout at the time, while Proofpoint CEO Sumit Dhawan shares how the company has scaled, evolved its platform, and stayed ahead of rapidly growing cyber threats in an AI-driven world. For more information on Thoma Bravo's Behind the Deal, visit https://www.thomabravo.com/behindthedeal Learn more about Thoma Bravo: https://www.thomabravo.com/ Learn more about Proofpoint: https://www.proofpoint.com/us Disclaimer: This podcast is for informational purposes only and does not constitute an advertisement. Views expressed are those of the individuals and not necessarily the views of Thoma Bravo or its affiliates. Thoma Bravo funds generally hold interest in the companies discussed. This podcast should not be construed as an offer to solicit the purchase of any interest in any Thoma Bravo fund. Certain statements about Thoma Bravo made by portfolio company executives are intended to illustrate Thoma Bravo's business relationship with such persons rather than Thoma Bravo's capabilities or expertise with respect to investment advisory services. Portfolio company executives were not compensated in connection with their podcast participation, although they generally received compensation and investment opportunities in connection with their portfolio company roles and in certain cases are also owners of portfolio company securities and or investors in Thoma Bravo funds. Such compensation and investments subject podcast participants to potential conflicts of interest. In addition, this podcast includes forward-looking statements. These statements are based on current expectations and assumptions and involve significant risks and uncertainties that could cause actual results to differ materially.