NeuralizeThe DevOps Platform for On-Device AI/ML

Neuralize - The On-Device AI Developer Platform

Streamlined Model Optimization Across End-User Devices

Key Features

• Benchmark models on real devices that we maintain
• Avoid spending time and money buying the latest devices and managing OS/SDK versions
• Specify optimization techniques with a few clicks
• Leverage the latest methods (quantization, palettization, pruning, etc.) across SDK/OS versions
• Evaluate performance trade-offs with our visualization tools
• Assess accuracy, inference speed, power consumption, and more through interactive charts and tables
• Integrate your existing devices and benchmarking setup
• Add benchmarks from your own devices by installing our software and importing our simple logging library

Use Cases

• Optimizing AI/ML models for deployment on consumer devices
• Benchmarking model performance across different hardware and software configurations
• Visualizing performance trade-offs to make informed optimization decisions
• Integrating with existing benchmarking setups for comprehensive performance analysis

Pricing

Contact us to request a demo and discuss pricing tailored to your specific needs and use cases.

Teams

Ciarán (CRO)

• Expertise: Cross-platform model inference optimization on consumer device platforms (Apple, Qualcomm, Intel, etc.)
• Experience: Building the world's first AI video codec at Deep Render and optimizing scientific simulations at ICHEC

Ivan (CTO)

• Expertise: On-device AI model optimization and compression techniques (quantization, palettization, pruning, etc.)
• Experience: Building the GenAI platform and pilot applications at Marshall Wace, Europe's leading hedge fund

Ismail (CEO)

• Expertise: Performance testing and quality assurance of AI-first apps with local inference on consumer devices
• Experience: Building applications for AR Glasses and VR headsets at Meta, and the world's first AI video codec at Deep Render

Get in touch to set up a meeting and explore how Neuralize can optimize your AI/ML models for on-device deployment.