Multi-agent orchestration with tool calling, shared state, human-in-the-loop gates, and governance hooks. From a single workflow to enterprise-scale ecosystems.
Training, fine-tuning, and deploying proprietary models on AWS and Azure. MLflow registries, feature stores, experiment tracking, CI/CD for models.
On-device and edge-scaled models for internal clients today, external tomorrow. Privacy-preserving, latency-sensitive, infrastructure-light.
Real-time vision pipelines, gesture control, voice interfaces, CAD-to-fabrication loops. Sub-300 ms camera-to-action for robotics and inspection.
Threat detection with agents, model security, adversarial robustness, and secure agent sandboxing. Bringing applied AI to the defensive layer.