Cribl and DeepTempo partner

On October 13, DeepTempo announced a strategic partnership with Cribl. Together, the companies are delivering an integrated solution that streamlines telemetry collection and unleashes deep learning-powered detection to stop polymorphic and agentic AI-driven threats.

At the core of the offering is Tempo, DeepTempo’s flagship platform. Tempo includes the company’s purpose-built LogLM, a foundation model developed by DeepTempo to understand the “language of logs,” along with the surrounding software and workflows needed for real-time, behavior-first detection. By combining Tempo’s advanced analytics with Cribl’s data collection and management capabilities, customers gain high-fidelity detections, faster investigations, and significant cost savings without the complexity of managing multiple collectors or preprocessing pipelines.

“Security teams need full visibility and the ability to act fast,” said Vlad Melnik, VP of business development and global alliances at Cribl. “With Cribl, organizations can shape and route telemetry to the right tools, like DeepTempo’s purpose-built deep learning engine, for real-time threat detection. It’s a natural fit: we deliver the right data, and Tempo extracts maximum security value.”

Security teams face an unprecedented challenge: the rapid growth of telemetry data combined with a new generation of polymorphic, AI-powered threats that evolve in real time. The partnership between DeepTempo and Cribl gives defenders a way to centralize control of their data and extract maximum security value from it without vendor lock-in or brittle, rule-bound detection pipelines.

“With Cribl’s data management and Copilot capabilities, pairing our Tempo platform at the network layer gives defenders both coverage and governance at scale,” said Evan Powell, CEO of DeepTempo. “Tempo’s LogLM turns raw telemetry into high-signal context, the insight security teams need to outpace agentic AI threats, zero-click exploits, and other attacks that slip past traditional defenses.”

Source: DeepTempo

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