Custom Cybersecurity AI Models
Train security models on your threat intelligence, incident data, and vulnerability records. Domain-specific fine-tuning for threat detection, investigation, and response tailored to your environment.
Cybersecurity Challenges
Alert fatigue and false positives
Evolving threat landscape
Skill shortage in security teams
Speed of response requirements
Data volume and complexity
How Custom Model Training & Distillation Solves Cybersecurity Challenges
Training domain models on curated corpora, applying NeMo and LoRA distillation, and wiring evaluation harnesses so accuracy stays high while latency and spend drop.
Domain-Specific Fine-Tuning
Train foundation models on your curated corpora for superior performance on specialized tasks.
Model Distillation
Compress large models into efficient variants using NeMo microservices and LoRA techniques.
Evaluation Harnesses
Automated testing frameworks measuring accuracy, latency, toxicity, and task-specific metrics.
Red Team Testing
Adversarial testing, jailbreak detection, and safety validation before production deployment.
Use Cases
- ✓Threat detection models trained on your network data
- ✓Incident triage models from your investigation history
- ✓Vulnerability prioritization from your asset context
- ✓Phishing detection fine-tuned on your email patterns
- ✓Malware classification from your threat intelligence
Key Benefits
Superior detection accuracy for your environment
Reduced false positives through environment-specific training
Lower inference costs for high-volume security data
Models that understand your network topology
Continuous improvement from SOC analyst feedback
Technology Stack
Ready to Deploy Custom Model Training & Distillation for Cybersecurity?
Let's discuss how our custom model training & distillation capabilities can address your cybersecurity challenges.
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