DeepTempo adds an AI‑powered behavioral detection layer to existing SIEM, NDR and telemetry stacks, using large language models to analyze logs and identify attacker intent, suspicious patterns, and novel threat behaviors that signature‑based tools miss. The platform provides real‑time alerts on AI‑driven automation, insider‑risk hijacks, signature‑less malware, and misuse of cloud services, integrating via APIs without requiring additional hardware.
Funding
Funding not disclosed
Founders
Product
Problem
Security teams struggle to detect modern AI‑driven and cloud‑based attacks because traditional tools rely on static signatures, manually maintained rules, and fixed baselines that cannot keep pace with rapidly changing attacker behavior.
Solution
DeepTempo provides an AI‑powered behavioral detection layer that integrates with existing SIEM, NDR, and telemetry stacks. By analyzing logs and telemetry with large language models, it identifies attacker intent, suspicious patterns, and novel threat behaviors that signature‑based systems miss. The platform surfaces these insights in real time without requiring additional hardware or replacement of current security tools. DeepTempo’s detection focuses on agentic automation, AI‑hijacked insiders, signature‑less malware, and the misuse of legitimate cloud services, helping defenders close blind spots and respond earlier to emerging threats.
Target Audience
Primary customers are security operations centers, SOC analysts, and threat detection teams in enterprises and critical infrastructure organizations that rely on SIEM and NDR solutions.
Features
- LogLM engine that ingests and parses heterogeneous log and telemetry data from existing security infrastructure
- Large language model analysis to uncover evolving threat behaviors and attacker intent beyond static IOCs
- Real‑time alerts that highlight suspicious activity patterns such as AI‑agent hijacks, automated attack sequences, and misuse of legitimate tools
- Seamless integration via APIs and connectors to SIEM, NDR, and other telemetry platforms, avoiding additional deployment complexity
- Continuous model updates that adapt to new attack techniques without manual rule changes