Catch attacks your NDR + SIEM can't
DeepTempo adds an intelligent detection layer to your security stack — powered by our LogLM, a vertical foundation model that continuously analyzes operational telemetry to detect cyberattacks at their earliest stage, including AI-driven campaigns and routine threats your current tools will never surface.
Cyberattacks have evolved. Detection hasn’t.
Attacks today are fast, stealthy, and adaptive, blending techniques across systems and hiding in normal traffic. Defenses built on rules, signatures, and anomaly models leave detection gaps. The result: extreme noise, undetected breaches, and high SOC costs.
Agentic attack automation
Attackers rotate infrastructure, domains, and tactics in hours. They test defenses, learn quickly, and evolve faster than you can update your detection rules.
Behavioral deception
With traffic encrypted, detection relies on behavioral signals. AI attacks now shape those signals, obscuring critical stages like C2 and exfiltration in plain sight.
AI agent hijacks
Enterprise AI agents access critical systems and data. They create a new insider-risk surface that traditional identity and endpoint controls were never designed for.
Signatureless malware
AI enables polymorphic attacks that change every time they run. Without stable indicators, rule- and IOC-based detection falls behind by design.
LOTL at machine speed
Automation lets attackers weaponize your own admin tools, cloud services, and SaaS APIs. Living off the land now happens faster than manual detection and response can track.
Incident scope expansion
Attacks move faster and touch more systems, identities, and APIs in minutes.What used to be a contained alert now becomes a multi-surface investigation
The intelligent detection layer for modern threats
DeepTempo is the detection layer your security stack is missing. Powered by our LogLM — our vertical foundation model purpose-built for security — it learns how your systems routinely operate and adds intent-level detection to your existing defenses, exposing stealthy attacks at their earliest stages before conventional tools react.
Detects evasive and AI-powered threats
Analyzes operational telemetry — from network flow and WAF logs to application-layer behaviors and threat intelligence feeds — to detect cyberattacks hiding in normal activity. Augments existing rules and ML models to decrease false positives and false negatives.
Early warning system for attacks
Detects threats before the boom by recognizing malicious intent such as reconnaissance, C2, credential access, etc. early in the kill chain, before your systems are actually exploited.
Reduces data and operational costs
Operates as an intelligent layer between your telemetry sources and SIEM, reducing the data you need to store while increasing the signal to act on. A self-learning vertical foundation model saves your detection engineering from additional rule writing or model maintenance.
Stays ahead of attackers
Learns from every environment it protects, with LogLM learning from new behaviors and attack patterns. This shared intelligence anticipates attacker moves and evolves faster than the threats it’s built to stop.
Protects everything
Defends every part of your environment — cloud, on-prem, OT, and critical systems. DeepTempo unifies visibility across hybrid environments and physical infrastructure, closing gaps in your current detection layer.
A detection layer built for modern systems
DeepTempo strengthens your detection stack without rip-and-replace. Deployed within your environment, the DeepTempo detection layer is interoperable with your NDRs, SIEMs, and security data lakes.
