At Pervizy, we're developing neural architectures specifically designed for embodied AI systems. Our models learn to perceive, reason, and act in the physical world with unprecedented efficiency.
Neural Architecture Visualization
Our models integrate visual, auditory, and tactile inputs to develop a unified understanding of the physical world, enabling robots to learn complex manipulation tasks.
Unlike traditional AI that requires massive compute for each decision, our architectures allocate computational resources dynamically based on task complexity.
Embodied AI requires split-second decisions. Our efficient models run directly on edge devices, enabling autonomous operation without cloud dependency.
We're not just building AI—we're reimagining how intelligent systems should be designed for the physical world.
Our novel sparse attention mechanisms and adaptive compute allocation reduce energy consumption by up to 90% compared to traditional architectures, without compromising on capability.
We develop general-purpose models that can be adapted to any embodied AI task—from robotic manipulation to autonomous navigation—providing a unified foundation for physical intelligence.
Our models are optimized to run directly on embedded hardware, enabling robots and autonomous systems to operate independently without cloud connectivity or centralized compute.
Environmental responsibility is core to our mission. Every architectural decision is made with energy efficiency in mind, contributing to a more sustainable future for AI.
Embodied AI requires split-second decisions. Our efficient architectures achieve sub-millisecond inference times, enabling responsive and reliable autonomous behavior.
Safety is paramount when AI operates in the physical world. Our models include built-in uncertainty quantification and fail-safe mechanisms for robust real-world deployment.
Embodied AI is AI that exists in and interacts with the physical world. Our foundational models are designed to power the full spectrum of capabilities that robots and autonomous systems require.
Advanced computer vision that interprets complex scenes, recognizes objects, and understands spatial relationships in real-time.
Fine-grained motor control enabling robots to handle delicate objects, use tools, and perform precise assembly tasks.
Audio processing for speech recognition, environmental sound understanding, and acoustic anomaly detection.
Autonomous path planning and obstacle avoidance using efficient simultaneous localization and mapping (SLAM).
Natural language understanding and gesture recognition for seamless human-robot collaboration.
Model-predictive control systems that anticipate environmental changes and plan actions accordingly.
“The measure of intelligence is the ability to change.”— Albert Einstein
Our energy-efficient foundational models power intelligent systems across diverse sectors, enabling sustainable automation at scale.
Power next-generation robots with energy-efficient models that enable real-time decision making and adaptive behavior in dynamic environments.
Learn moreOptimize production lines with AI that learns from physical processes, reducing waste and energy consumption while maximizing output quality.
Learn moreEnable compassionate care robots with models that understand human emotion, movement, and medical protocols with minimal power draw.
Learn moreTransform supply chains with embodied AI that optimizes routes, handles packages, and coordinates warehouses using 90% less compute.
Learn moreDeploy solar-powered AI systems that monitor crops, manage irrigation, and harvest with precision in remote locations.
Learn moreBuild autonomous systems for extreme environments where energy efficiency is critical and human intervention is impossible.
Learn moreCreate intelligent home assistants that understand context, learn preferences, and operate efficiently on edge devices.
Learn moreDeploy AI-powered sensors and drones that track ecosystems, wildlife, and climate patterns with minimal ecological footprint.
Learn moreEnable safe human-robot collaboration in workplaces with AI that predicts intentions and adapts to human partners in real-time.
Learn moreTraining a single large language model can emit as much carbon as five cars over their entire lifetimes. As AI systems become more prevalent, this environmental impact will only accelerate—unless we fundamentally rethink how we build intelligent systems.
At Pervizy, we believe that efficiency isn't just an engineering constraint—it's an ethical imperative. Our research demonstrates that with the right architectural innovations, we can achieve remarkable capabilities while dramatically reducing computational requirements.
For embodied AI in particular, energy efficiency isn't optional. Robots and autonomous systems must operate on limited battery power, often in remote or resource-constrained environments. Our foundational models are designed from the ground up to maximize intelligence per watt.
Our models are designed to achieve state-of-the-art performance while targeting 90% less energy consumption than comparable systems.
Through advanced compression and architecture design, we aim to create models up to 10x smaller without sacrificing capability.
Reduced computational requirements can mean significantly lower thermal output, enabling deployment in constrained environments.
Lower energy and hardware requirements are designed to translate to significant cost savings at scale.
Our research is driven by a singular mission: making embodied AI accessible and sustainable. Here are some of our recent contributions to the field.
We are developing a novel sparse attention architecture designed to enable embodied AI systems to focus computational resources only on task-relevant inputs, targeting up to 12x inference speedup with minimal accuracy loss.
This work presents our framework for dynamic compute allocation that adjusts model capacity in real-time based on environmental complexity, designed to enable autonomous robots to operate efficiently across diverse scenarios.
Our upcoming work explores breakthrough approaches in multimodal AI—combining vision, audio, and proprioception with linear rather than quadratic computational complexity, designed to make rich sensory integration feasible on edge devices.
The future of AI isn't just about intelligence—it's about sustainable intelligence that works in harmony with our world.
At Pervizy, we believe that the most powerful AI systems should also be the most efficient. The current trajectory of AI development—requiring ever-larger models and ever-more compute—is unsustainable, both environmentally and economically.
Our research focuses on developing foundational models that can power embodied AI—robots, autonomous vehicles, and intelligent machines—while using a fraction of the computational resources required by traditional approaches. This isn't just an engineering challenge; it's a moral imperative.
We envision a future where intelligent machines are ubiquitous—not because they're connected to massive data centers, but because they carry efficient, capable AI with them. Where a delivery robot can operate all day on a single charge, and a prosthetic limb can respond with the speed and precision of natural movement.
By 2030, we aim to have our energy-efficient AI powering millions of embodied systems worldwide—from healthcare robotics to sustainable agriculture—while maintaining a net-zero carbon footprint across all operations.
Join us in creating energy-efficient AI that will power the embodied intelligence of tomorrow. Whether you're a researcher, engineer, or organization—there's a place for you in our mission.
We are looking for exceptional researchers, engineers, and thinkers who share our vision for sustainable AI.
View OpeningsExplore our published papers and technical reports on energy-efficient embodied AI systems.
View PapersCollaborate with Pervizy to bring efficient AI to your robotics, automation, or autonomous systems.
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