Custom ML model development for specialized domains where off-the-shelf solutions fall short. We build models for signal classification, anomaly detection, time-series forecasting, and pattern recognition across RF, sensor, and operational data streams.

Physics-informed neural networks and surrogate models that accelerate simulation workflows. Edge AI deployment for embedded systems with limited compute. Model architecture design, training, optimization, and production deployment with uncertainty quantification and interpretability built in.

Large language model applications and autonomous AI agents for document processing, decision support, and intelligent automation. We build copilots and chatbots for internal knowledge management, customer support, and operational assistance.

Integration patterns for connecting AI systems with enterprise tools and data sources. Knowledge retrieval pipelines that ground AI responses in organizational context. Production-ready deployments that scale from pilot projects to organization-wide rollout.

Coordination algorithms for multi-agent systems including drone swarms and distributed sensor networks. Decentralized decision-making for area coverage, target search, and dynamic obstacle avoidance without centralized control.

Autonomous agents that reason, plan, and execute complex tasks. From single-agent automation to multi-agent coordination, we build systems that operate reliably in dynamic environments where human-in-the-loop isn't always possible.