Accelerating the Workflows needed to achieve Machine Speed Intelligence
From threat intelligence to incident response, one Defense Platform powered by LogLM. Vigil, the open source AI SOC started by DeepTempo, is included — and pluggable, so any AI SOC works.
No rip and replace. No leap of faith.
DeepTempo starts inside the operations you already trust and makes them more intelligent. Automation earns its way forward. Attempt, verify, repeat, until detection and response run at the speed of the attack.
Slide the slider to see how MTTD and MTTR accelerate as trust compounds.
Automate reactive threat hunts with Vigil
Drop your existing workflows into Vigil, use the provided agents, and bring your own local LLM — within a day you are accelerating. Run queries across the systems you already have, and use the LogLM to ingest logs at volume and find the patterns of life others miss.
Drop the LogLM into your data lake or Cribl
Run detection upstream of the SIEM. You immediately start seeing attacks you have been missing — and start saving money by focusing the SOC on real incidents and cutting the ingestion of logs that were never very useful.
Accelerating towards machine speed intelligence
Threat intelligence
Rather than replace the feeds you already trust, LogLM treats them as inputs and predicts which infrastructure will be weaponized from behavioral signatures in your own telemetry, often hours before commercial feeds tag it. Vigil, or your AI SOC, turns the signal into campaign narratives and board briefs.
How it helps:
- Finds attacker intent in the telemetry you already collect
- Alerts to malicious activity early in attack lifecycle
- Uncovers C2 channels and covert infrastructure, even when encrypted
- Integrates threat intelligence as an optional signal
Proactive threat hunting
Because LogLM has embedded your activity into a TTP-aligned space, a hunt becomes a vector query that returns in sub-second time and finds variants no signature describes. Senior hunters now oversee agents that hunt with the model, and the learning loop captures what each hunt finds.
How it helps:
- Contextual explanations for each detection
- Sequence of events, and entities involved
- ATT&CK mapping for faster triage and response
- ChatOps for natural language investigation
Incident identification
Instead of relying only on manually maintained rules and static baselines, LogLM identifies even rapidly evolving attacks as sequences across your existing telemetry, zero-shot on day one and sharper with exposure. Ongoing efficacy measurement can be applied to your existing detections too, for a comprehensive understanding.
How it helps:
- Up to 99% zero-shot performance on initial deployment
- Detection accuracy improves continuously as environments evolve
- Reduces manual rule-writing, threshold tuning, and detection maintenance
- Learns from evolving attacker behavior patterns across deployments
Incident response and forensics
Because LogLM keeps activity embedded, every finding arrives as a story, and Vigil or your AI SOC assembles that context from its findings, cutting reconstruction time. The same record can be investigated at any point in the past, so today's model finds attacks that were invisible at the time.
How it helps:
- 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
Works with your existing stack
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.
How it helps:
- Smart telemetry reduction lowers SIEM cost
- No manual rule writing or retraining
- Faster investigation and resolution cycles
- Slack integration for quick analyst collaboration
Proven across large enterprise environments
Examples of attack behaviors DeepTempo can identify
DeepTempo is designed to scale across large telemetry environments while maintaining fast detection response times and reducing operational overhead for security teams.
- 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
Integrates with existing security infrastructure
DeepTempo works alongside existing SIEMs, NDRs, cloud environments, telemetry platforms, and security data lakes without requiring organizations to replace their existing tools.