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Distributed Edge based surveillance architecture
A scalable, hybrid AI surveillance platform that combines distributed edge-based real-time detection with centralized intelligence to enable multi-camera, multi-domain monitoring systems. The leopard detection system is built on similar architecture where:
100+ edge devices forming a private cloud, perform real-time inference in the field
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Selectively transmit insights
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Integrate with a centralized edge cloud platform
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Enabling scalable, intelligent surveillance across environments
Centralized workstation based multi-stream inference architecture
A centralized AI inference system where multiple cameras are connected to a high-performance workstation (GPU-based) to process video streams at scale.
Designed to achieve below:
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Supporting more cameras per system
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Increasing total surveillance coverage
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Enabling higher compute capacity for AI models
DeepManthan Conversational AI platform
DeepManthan conversational AI platform, showcases its ability to provide real-time operational insights through natural language conversations. It acts as an agnostic "agentic insight-bridge," connecting to any private or third-party AI infrastructure and data tools.
This platform empowers operational teams—like site managers or forest rangers—to manage and query complex distributed AI infrastructure and data using simple, direct conversation, eliminating the need for technical skills to access real-time status and visual ground truth.
Advanced R&D Lab system architecture for Academia
A unified, multi-domain R&D platform combining specialized compute pods with centralized infrastructure to support AI, systems and advanced technology experimentation.
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AI/ML & LLM training
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Computer vision & digital twins
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IoT & distributed systems
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Data science & analytics
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Cybersecurity (including air-gapped testing)
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Blockchain & quantum computing
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