DeepTempo, a pioneer in behavioral threat detection powered by deep learning, will participate at CrowdStrike Fal.Con 2025 in Las Vegas alongside Cribl. DeepTempo team members will be available onsite to demonstrate how their foundation model, LogLM, counters AI-enabled adversaries and integrates with the Cribl platform to enhance enterprise defenses against modern threats.
The speaking session, titled Defending Against Modern Threats with Cribl & DeepTempo, will feature a brief company introduction followed by discussions on current and future integrations with the Cribl platform. Craig Stancill will highlight real-world use cases and examples of how DeepTempo’s LogLM delivers superior detection and response outcomes in security operations. The sessions are scheduled for Tuesday, September 16, at 10:00 a.m. PT, and Wednesday, September 17, at 1:00 p.m. PT, at Cribl Booth #1718 in the Caesars Forum, Las Vegas.
Key participants include Evan Powell, CEO of DeepTempo; Craig Stancill, Director of Product Management; and Fred Smith, Vice President of Business Development. As adversaries leverage AI rapidly, security teams require AI-native defenses tailored to real-world telemetry. DeepTempo’s LogLM, trained on network data, provides differentiated detection to help defenders match the pace of threats.
The event underscores the importance of integrated solutions in cybersecurity, where DeepTempo’s deep-learning-based offerings safeguard enterprises and service providers against cyberattacks. By combining LogLM with Cribl, organizations can optimize security spending, enhance operational efficiency, and maintain robust protection without vendor lock-ins.
DeepTempo offers deep-learning-based cybersecurity solutions that safeguard enterprises and service providers against cyberattacks. Leveraging its foundation LogLMs, the company’s cybersecurity solutions are on the Snowflake Native App Marketplace and also available for deployment in on-premise security data lakes, helping organizations optimize security spending and enhance operational efficiency while maintaining robust threat protection without lock-ins.
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