Building domain-agnostic agentic system for enterprise decisioning, anomalous event detection, and adaptive pattern learning. Horizontal solution deployable across industries with self-learning capabilities and explainable decision paths.

Building production-ready multi-agent systems for autonomous data pipeline management. Industry-agnostic framework that handles data quality, orchestration, and monitoring with AI agents collaborating in real-time.

Developing cryptographic proof systems for secure, privacy-preserving verification at scale. Focus on trustless validation mechanisms and distributed consensus for identity and data integrity use cases.

Advancing the field-theoretic approach to context modeling in AI systems. Working on efficient implementation patterns and real-world validation across enterprise use cases.

Exploring satellite data analytics and distributed space infrastructure patterns. Investigating real-time processing architectures for LEO satellite constellations and geospatial intelligence applications.