Neuralize

On-Device AI Made Easy

Deploy AI models into your applications, with local inference, but without the hassle.

On-Device AI Made Easy

Deploy AI models into your applications, with local inference, but without the hassle.

We provide tools and services for your entire on-device AI pipeline

Maintenance

Ensure models stay optimized as platforms and dependencies change

SDK & OS Version Updates

New Device Releases

Frequent App Updates

Maintenance

Ensure models stay optimized as platforms and dependencies change

SDK & OS Version Updates

New Device Releases

Frequent App Updates

Benchmarking

Assess model accuracy and efficiency for optimal deployment decisions

Test Across Many Devices

Understand Model Viability

Track Model Version Progress

Benchmarking

Assess model accuracy and efficiency for optimal deployment decisions

Test Across Many Devices

Understand Model Viability

Track Model Version Progress

Fine-Tuning

Improve model capabilities for your use case, while maintaining efficiency

Tailored Model Capabilities

LoRA Adaptation

Local Fine-Tuning

Fine-Tuning

Improve model capabilities for your use case, while maintaining efficiency

Tailored Model Capabilities

LoRA Adaptation

Local Fine-Tuning

Optimization

Improve inference efficiency while maintaining model capabilities

Model Compression

Inference Acceleration

Maintaining Model Capabilities

Optimization

Improve inference efficiency while maintaining model capabilities

Model Compression

Inference Acceleration

Maintaining Model Capabilities

Integration

Deploy models into your AI-native app with local, on-device inference

Pre/Post Processing

Runtime Selection

Minimal Code Additions

Integration

Deploy models into your AI-native app with local, on-device inference

Pre/Post Processing

Runtime Selection

Minimal Code Additions

Conversion

For inference in Apple (iOS/MacOS), Android and Windows apps

Convert Python Models

Leverage HW Acceleration

Device-Specific Optimization

Conversion

For inference in Apple (iOS/MacOS), Android and Windows apps

Convert Python Models

Leverage HW Acceleration

Device-Specific Optimization

Conversion

For inference in Apple (iOS & MacOS), Android and Windows applications

Convert Python Models

Leverage HW Acceleration

Device-Specific Optimization

Optimization

Improve inference efficiency while maintaining model capabilities

Model Compression

Inference Acceleration

Maintain Model Capability

Fine-Tuning

Improve model capabilities for your use case, while maintaining efficiency

Tailored Model Capabilities

LoRA Adaptation

Local Fine-Tuning

Pre/Post Processing

Runtime Selection

Minimal Code Additions

Integration

Deploy models into your AI-native app with local, on-device inference

Maintenance

Ensure models stay optimized as platforms and dependencies change

SDK & OS Version Updates

New Device Releases

Frequent App Updates

Benchmarking

Assess model accuracy and efficiency for optimal deployment decisions

Test Across Many Devices

Understand Model Viability

Track Model Version Progress

Tools and services for your entire pipeline

Maintenance

Ensure models stay optimized as platforms and dependencies change

SDK & OS Version Updates

New Device Releases

Frequent App Updates

Benchmarking

Assess model accuracy and efficiency for optimal deployment decisions

Test Across Many Devices

Understand Model Viability

Track Model Version Progress

Fine-Tuning

Improve model capabilities for your use case, while maintaining efficiency

Tailored Model Capabilities

LoRA Adaptation

Local Fine-Tuning

Optimization

Improve inference efficiency while maintaining model capabilities

Model Compression

Inference Acceleration

Maintaining Model Capabilities

Integration

Deploy models into your AI-native app with local, on-device inference

Pre/Post Processing

Runtime Selection

Minimal Code Additions

Conversion

For inference in Apple (iOS/MacOS), Android and Windows apps

Convert Python Models

Leverage HW Acceleration

Device-Specific Optimization

Conversion

For inference in Apple (iOS & MacOS), Android and Windows applications

Convert Python Models

Leverage HW Acceleration

Device-Specific Optimization

Optimization

Improve inference efficiency while maintaining model capabilities

Model Compression

Inference Acceleration

Maintain Model Capability

Fine-Tuning

Improve model capabilities for your use case, while maintaining efficiency

Tailored Model Capabilities

LoRA Adaptation

Local Fine-Tuning

Pre/Post Processing

Runtime Selection

Minimal Code Additions

Integration

Deploy models into your AI-native app with local, on-device inference

Maintenance

Ensure models stay optimized as platforms and dependencies change

SDK & OS Version Updates

New Device Releases

Frequent App Updates

Benchmarking

Assess model accuracy and efficiency for optimal deployment decisions

Test Across Many Devices

Understand Model Viability

Track Model Version Progress

Our team has expertise across the on-device AI stack

We have expertise across the stack

Our team has expertise across the on-device AI stack

Ciarán (CRO)

Conversion

Optimization

Background: Cross-platform model inference optimization for consumer device platforms

Ivan (CTO)

Integration

Fine-Tuning

Background: Development of fine-tuned AI applications and low latency processing systems

Ivan (CTO)

Integration

Fine-Tuning

Background: Development of fine-tuned AI applications and low latency processing systems

Ismail (CEO)

Benchmarking

Maintenance

Background: Product testing and deployment for AI applications in resource constrained devices

Ciaran (CRO)

Conversion

Optimization

Background: Cross-platform model inference optimization for consumer device platforms

Ismail (CEO)

Benchmarking

Maintenance

Background: Product testing and deployment for AI applications in resource constrained devices

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Neuralize

On-Device AI Made Easy

Deploy AI models into your applications, with local inference, but without the hassle.