PhysicalAI for Autonomous
Sensing at the Edge

Real-time, multi-modal sensor fusion for mission-critical defense and enterprise operations

CUAS Counter Drone System Image

Introducing FuzionAI

A Reinforcement Learning-driven sensor fusion platform that combines electromagnetic signals, thermal imaging, and video inputs to deliver high-confidence target detection at the network edge—with no cloud dependency.

Multi-Modal Fusion

Seamlessly integrates RF/electromagnetic, thermal, and visual sensors into a unified perception system for unparalleled situational awareness.

Edge Computing

Operates independently at the network edge with zero cloud dependency, ensuring low-latency responses critical for defense operations.

RL-Driven Intelligence

Reinforcement learning architecture that continuously adapts and improves detection accuracy across diverse operational environments.

Mission-Critical Applications

From protecting critical infrastructure to enabling autonomous operations, FuxionAI delivers intelligence where it matters most.

Defense Applications

  • Counter-UAS Operations

    Real-time detection and classification of low, slow, and small (LSS) drones threatening civilian and military installations.

  • Jammer Detection & Avoidance

    Enable drones and autonomous systems to detect and intelligently navigate around electromagnetic interference zones.

  • Perimeter Security

    Multi-layered threat detection for forward operating bases, critical infrastructure, and secure facilities.

  • Autonomous ISR

    Intelligence, surveillance, and reconnaissance missions with AI-driven contextual awareness and decision support.

Enterprise Applications

  • Intelligent Inspection

    Autonomous drones and robots perform complex infrastructure inspections with contextual guidance and anomaly detection.

  • Campus & Facility Monitoring

    Comprehensive security and operational monitoring for corporate campuses, data centers, and industrial facilities.

  • Fire & Hazard Detection

    Early warning systems combining thermal and visual analysis for rapid fire detection and emergency response.

  • Infrastructure Monitoring

    Continuous monitoring of power grids, pipelines, and transportation networks with predictive maintenance insights.

Team

Led by experts in AI, robotics, and defense technology with deep domain expertise.

Rajesh Rasalkar

Rajesh Rasalkar

Co-Founder

Rajesh Rasalkar is a seasoned Wireless AI/ML Architect with 25 years at Meta, Oracle, and Bell Labs, holding multiple patents in Edge Cloud Computing.

Dr. Vignesh Manohar

Dr. Vignesh Manohar

Co-Founder

PhD in machine learning, computer vision, and signal processing, CTO

Dr. Craig Kleski

Dr. Craig Kleski

Co-Founder

PhD in Mathematics, Univ. of Virginia (UVA) using machine learning/deep learning, computer vision, control, and meta-learning

Amit Tiwari

Amit Tiwari

Co-Founder

Entrepreneur and seasoned Executive -- Drove multiple Cloud, Networking startups to unicorn outcomes. Affirmed Networks - acquired by Microsoft, Starent Networks – IPO & then acquired by Cisco

Raj Narayan

Raj Narayan

Co-Founder

Serial entrepreneur with a Master’s in Economics, known for building and scaling high-impact technology ventures. Founder with multiple successful exits.

Press & Media

Latest announcements, news coverage, and educational webinars

Announcement February 2, 2026

PhoenixAI & VirginiaTech Announce Collaboration for Advancing Software-Based Anti-Jamming for Autonomous Robotics

Building autonomous robots and drones that can sense, learn, and adapt in real time when deployed in environments of GPS denial, RF interference, and adversarial jamming.

Read Full Release →
Announcement October 12, 2025

PhoenixAI partners with Atriano for global deployment of AI-Powered defense solutions

PhoenixAI combines it's breakthrough Multi-Sensor Fusion technology with Atriano’s global execution network — bringing mission-ready, intelligent defense solutions to governments and enterprises worldwide.

Read Full Release →
Press Release July 15, 2025

PhoenixAi Tech: 3D Drone Mapping with Edge Computing

We’re excited to announce the successful launch of out AI/ML tech that brings together drones, stereo vision, and 3D reconstruction.

Read Full Release →
Announcement February 22, 2025

5G Command & Control: Redefining Drone Connectivity

PhoenixAI’s 5G-based Command and Control (C2) enables low-latency, high-bandwidth, and fully encrypted connectivity for smarter, safer, and more autonomous drone missions.

Read Full Release →
Research Paper December 15, 2024

Reinforcement Learning Enabled UAV Path Planning to Optimize Cellular Connectivity

Drones, especially when flown Beyond Visual Line of Sight (BVLOS) need areas of good cellular (4G/5G) connectivity, thereby necessitating careful path planning. The dynamic nature of the wireless channel combined with the base station antenna beams oriented to serve only ground terminals significantly increases the probabilities of drones losing connectivity. This paper proposes a reinforcement learning (RL) model that enables a drone in a cellular (i.e., 4G or 5G) environment to learn from the RF environment it flies in, and determine the best flight path based on its characteristics. Specifically, we employ a Q-learning approach that can be trained offline to optimize link quality, handoffs and distance, and be deployed on the drone with minimal computing requirements.

Read on IEEE Spectrum →
Announcement November 30, 2024

Introducing PhoenixAI P-NEXUS — Jamming-Proof, GPS-Denied Edge Autonomy for 5G Airspace

PhoenixAI P-NEXUS is fully integrated, TAA/NDAA-compliant Edge Autonomy AI Stack built to accelerate next-gen drone and robotics development. P-NEXUS combines Pixhawk flight control, NVIDIA Jetson Nano edge compute, 5G modem, and global eSIM into a plug-and-play platform that removes integration complexity and unlocks resilient, software-defined autonomy.

Read Full Release →
Research Paper October 15, 2024

RL Based UAV Trajectory Optimization to Avoid Jammers and Optimize Wireless Connectivity

Drones have found extensive use in military applications. Avoiding enroute RF jammers that can saturate the RF receiver and inhibit communication is a major challenge. Additionally, GNSS jammers can render drones completely nonfunctional by not allowing the drone to communicate with GPS satellites to ascertain their location. This work addresses these challenges by developing a reinforcement learning (RL) algorithm that is able to optimize the wireless connectivity while avoiding jammers along the drone route. Notably, the algorithm ensures minimal deviation from the planned path in the presence of jammers.

Read on IEEE Spectrum →
Webinar June 28, 2024

Enhancing Drone Security with AI-Powered Anti-Jamming Technologies

Drones are vulnerable to malicious jamming technologies that can disrupt critical operations. Learn more about PhoenixAI's patented software based algorithm technology for anti-jamming.

Watch on YouTube
Webinar Feb 23, 2024

Future of AI-Powered Drones

Join our CTO and Head of AI Research Vignesh Manohar as they demonstrate FuzionAI's capabilities and discuss the future of AI-Powered Drones and edge-based autonomous sensing.

Watch on YouTube
Press Release Feb 15, 2024

ACL Digital and PhoenixAI.tech Partner to Take AI-Driven Drone Technology to New Heights

The strategic partnership enhances ACL Digital’s capabilities with PhoenixAI.tech, focusing on AI drone solutions for UAVs, IoT, and edge computing to revolutionize operations significantly Beyond Visual Line of Sight (BVLOS) missions.

Read Full Release →

Blogs

Latest articles, research papers, and industry insights

Trillion Sensor Economy
Industry Insights • January 10, 2026 • 14 min read

The Trillion Sensor Economy

How PhoenixAI unlocks the world's most underutilized data asset

Read More →
Embodied AI
Industry Insights • Nov 23, 2025 • 9 min read

Embodied AI

Intelligence That Perceives, Reasons, and Acts in the Physical World

Read More →
Fusion-ISR F100
Product Updates • Nov 23, 2025 • 25 min read

Introducing PhoenixAI Fusion-ISR F100

AI-driven multi-sensor fusion platform for autonomous aerial counter-UAS operations

Read More →
Reinforcement Learning for UAV Trajectory Optimization
Research Paper • Oct 14, 2025 • 25 min read

Reinforcement Learning for UAV Trajectory Optimization

Avoiding jammers while optimizing wireless connectivity through reinforcement learning

Read More →
Physical AI
Industry Insights • September 22, 2025 • 9 min read

Beyond Robotics: The Future of Physical AI

How general-purpose intelligence is transforming our understanding and interaction with the physical world

Read More →
Invisible War
Industry Insights • August 11, 2025 • 9 min read

Winning the The Invisible War

Sensor Fusion Is Critical for Counter-Drone Defense

Read More →
AI Edge Computing
Technology • August 11, 2025 • 22 min read

PhoenixAI Edge Computing for Autonomous Drone Operations

Enhancing Military UAS Capabilities Through Distributed AI Intelligence

Read More →
Network AI
Industry Insights • June 10, 2025 • 9 min read

Rethinking Networks for the Age of Physical AI

Why Today's Networks Are Misaligned with the AI Era—and What PhoenixAI Is Doing About It

Read More →
Fuzion Platform
Industry Insights • March 14, 2025 • 15 min read

Introducing PhoenixAI’s Fuzion Platform

Understanding the Physical World Through Sensor Fusion and Edge Intelligence

Read More →
Multi-Modal Sensors
Technology • October 17, 2024 • 8 min read

The Future of Multi-Modal Sensor Fusion

How combining RF, thermal, and visual sensors creates unprecedented situational awareness for autonomous systems operating at the network edge.

Read More →
Counter UAS
Defense • August 7, 2025 • 6 min read

AI-Enabled RF Passive Sensing for Counter-UAS

Augmenting computer vision techniques to solve the scale-range ambiguity problem.

Read More →
Edge AI
Industry Insights • July 5, 2024 • 10 min read

Edge AI: Why Latency Matters in Defense

Understanding the critical importance of edge computing for defense applications where milliseconds can mean the difference between success and failure.

Read More →