An intent-aware detection layer for the modern SOC
DeepTempo adds a detection layer that turns telemetry into precise, MITRE-mapped detections — powered by a vertical foundation model with end to end validation.
A self-learning detection layer
An intelligent layer that converts operational telemetry into real-time detections.
No rules to write or model tuning to maintain. Accuracy reporting and adaption.
A precise Detection Layer with built in reporting and adaptation.
Catches early-stage attacker intent accurately
The LogLM understands what normal looks like - without significant retraining in your environment. The detection layer identifies attacker intent early in the kill chain and surface threats before SIEM or NDR tools can react.
Key features:
- Detects attacker intent from telemetry with extreme accuracy
- Alerts to malicious activity early in attack lifecycle
- Uncovers C2 channels and covert infrastructure, even when encrypted
- Integrates threat intelligence as an optional signal
Reveals threat context that matters
DeepTempo delivers reliable detections complete with context that is immediately actionable by SOC analysts. Each detection includes clear reasoning and is mapped to MITRE ATT&CK mapping so analysts can trust the results and act faster.
Key features:
- Contextual explanations for each detection
- Sequence of events, and entities involved
- ATT&CK mapping for faster triage and response
- ChatOps for natural language investigation
Auto-tunes to your environment
DeepTempo's Detection Layer generalizes across environments. It starts strong with high zero-shot accuracy and adapts to new tools, workloads, and infrastructure. The Detection Layer measures accuracy of all detections end to end. This reduces operational burdens and delivers high accuracy at scale.
Key features:
- 85% zero-shot accuracy on the first deployment
- Detection Layer improves accuracy over time
- Minimal manual tuning overheads or training costs
- Collective defense improves results globally
Consistent protection across every environment
DeepTempo delivers agentless threat detection across cloud, data center, remote, and OT environments. It detects east-west movement, maps communication paths automatically, and scales to petabytes of log data — ensuring attackers can’t hide in internal traffic.
Key features:
- Flow-based visibility across hybrid environments
- East-west detection without any agents to deploy
- Automatic communication mapping for attack path discovery
- Scales to petabyte-scale deployments
Stronger protection, lower operational costs
By operating directly on your data lake, and filtering high-value signal before it reaches your SIEM, DeepTempo cuts ingestion and storage costs without losing visibility. Detection engineers spend less time tuning and more time responding, with optional Slack-based ChatOps for rapid collaboration.
Key features:
- Smart telemetry reduction lowers SIEM cost
- No manual rule writing or retraining
- Faster investigation and resolution cycles
- Slack integration for quick analyst collaboration
Proven accuracy and scale in large enterprise environments
Model Performance
DeepTempo’s LogLM architecture has shown consistent, verifiable results across controlled customer environments, proving that deep learning-based threat detection can outperform rule-based systems in both accuracy and operational efficiency.
- 99% detection rates for most common TTPs (e.g. Command & Control)
- 85%+ accuracy on day one, improving to 94%+ after adaptation
- Less than 5% false positives, significantly reducing alert noise
- Sub-second detection latency across petabytes of data
- Up to 45% lower SIEM cost through telemetry reduction
Works with your existing stack
DeepTempo integrates with your existing cloud, security stack, SIEM, and data lake infrastructure, running upstream of your detection and response systems.