Triago handles the queue. Huntra hunts the threats already inside. GPU-accelerated causal analytics on TB-scale historical telemetry, running 24 hours a day, without requiring a single dedicated threat hunter.
Reactive triage only catches the alerts that fire. Living-off-the-land attacks, slow credential theft, and memory-only implants are designed specifically to not fire alerts. Finding them requires hunting through historical telemetry looking for behavioral patterns, not signatures. That's work that requires time no analyst actually has.
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RAPIDS cuDF pulls TB-scale SIEM, EDR, DNS, proxy, and flow data into GPU memory. Incremental, CDC-based.
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cuML GPU clustering builds behavioral baselines per entity. Deviations are scored and ranked.
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NeMo-tuned hunt agents generate and rank hypotheses from anomalous entities, grounded in MITRE ATT&CK.
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Agents pivot through cuGraph causal chains. Confirmed findings fire a Triago alert with full evidence.
Billion-edge entity graph traversal in seconds. BFS from any anomalous host finds lateral movement chains that manual queries miss entirely. CPU-based tools need hours for the same traversal.
CPU: hours · Huntra: seconds
"Why did this lateral movement occur?" Huntra traces intervention chains, not just correlation.
Weekly report showing which MITRE techniques your telemetry can and cannot detect.
2,000+ hunt hypotheses tuned on the Triago attack-trace corpus. Novel techniques are added from Forgen synthetic simulations. Huntra runs them all, continuously, ranked by probability.
Confirmed hunt findings create Triago alerts automatically. No copy-paste. Your team handles the verdict; autonomous response handles containment.
| Workload | GPU technology | Why CPU fails |
|---|---|---|
| TB-scale telemetry ETL | RAPIDS cuDF (H100) | CPU Pandas on 10 TB/day takes 4-6 hours. RAPIDS finishes in under 15 minutes. |
| Behavioral clustering | RAPIDS cuML | 100M+ entity-event tuples per day. CPU ML cannot run at SOC throughput. |
| Lateral movement tracing | RAPIDS cuGraph (H100) | Billion-edge BFS on CPU takes hours. cuGraph runs in seconds. |
| Hunt agent inference | TensorRT + Triton | Sub-50ms behavioral scoring per entity at scale. CPU latency is 10-50x higher. |
| Model fine-tuning | NeMo + DGX H100 | Weekly RL training on hunt corpus. Multi-GPU runs required at model scale. |
Hunt findings auto-escalate to Triago for autonomous investigation and containment. No handoff delay.
Huntra pulls actor attribution and attack-path context from Grafex in real time during active hunts.
Huntra hypothesis models are pre-trained on synthetic hunt scenarios generated by Forgen's adversarial simulation.
No dedicated threat hunter needed. A pilot gives you a coverage gap report and, if anything is hiding in there, a confirmed finding before you sign anything.