The AI defense platform for IT, OT & cloud
Our LogLM is state of the art in finding today's attacks, a purpose built AI foundation model. Vigil is the leading open source AI SOC. They work together, or separately, to add machine speed intelligence to your environment.
Built with teams who can't afford to miss
BNY helped us build the LogLM — partnering from the earliest days to train and pressure-test the model against the scale and rigor of one of the world's largest banks.
Deutsche TelekomDeutsche Telekom initiated a project to protect themselves and their customers from AI-powered attacks. We have collaborated to deliver a solution that is proven to outperform signature-based detections while catching advanced attacks rapidly, and with low false positives.
StanfordUniversities are among the hardest environments to protect — open by design and enormous in scope. We collaborate directly with Stanford's cyber teams on defending them.
We partner with TAC on OT management. Attackers are increasingly going after critical infrastructure, and prior approaches cannot rapidly see or respond to these attacks.
One platform layer across the security stack
DeepTempo plugs into the telemetry and tools already in place. LogLM does the detection. Vigil turns findings into analyst workflow. SOCBench measures quality and drift.
Policy and signature rules still matter. They are no longer enough.
Questions to ask any AI SOC vendor
Are detections based on a purpose-built model, or just prompts over someone else's LLM?
We spent well over a year building LogLM as a foundation model for telemetry before releasing it. Agents wrapped around a generic LLM inherit its blind spots and its false positives.
Can your team read the code?
Vigil is open source. Your analysts can read every agent and playbook, and extend them. No black box sits between your SOC and its own judgment.
Do you have to disrupt operations to start?
No. DeepTempo runs upstream of your SIEM, in your data lake or Cribl pipeline, and inside the workflows your SOC already runs. Nothing gets ripped out. It just gets more intelligent.
How does automation earn trust?
Attempt, verify, repeat. Our team learned this building StackStorm, the automation platform used across large enterprises. Autonomy is earned.
Do we need labeled data or months of tuning before it works?
No. LogLM is pretrained on telemetry. A Detection Assessment runs on your historical logs from day one, with no labels and no training project.
Does DeepTempo replace our SIEM?
No. It runs upstream of the SIEM, surfaces the attacks rules miss, and cuts low-value ingestion. The SIEM you already own gets cheaper and sharper.
Does our data leave our environment?
No. Model weights, verdicts, and learning stay inside your environment. Bring your own cloud, run on-prem, or use your own local LLM in Vigil.
How do you prove an AI SOC actually works?
With an open benchmark. SOCBench measures precision, recall, false positives, MITRE coverage, cost, and drift for any detection stack, including ours.
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.
