Transform AI withFoundation Model Compression
Our advanced distillation techniques reduce LLM size by up to 70% while maintaining performance, enabling faster inference and dramatically lower costs.
70% Size Reduction
Our distillation techniques produce models that are a fraction of the original size.
2-4x Faster Inference
Smaller models mean dramatically improved inference speed and lower latency.
Preserved Capabilities
Maintain performance and capabilities across key benchmarks and tasks.
Smaller Models, Uncompromised Performance
Using our innovative distillation techniques, we drastically reduce model size while preserving the capabilities that matter most for your use case.
Smart Compression
We identify and preserve the most important weights and connections while eliminating unnecessary complexity.
Targeted Distillation
Our technology focuses on distilling key capabilities rather than general compression, maintaining domain-specific performance.
Optimized Inference
Get dramatically faster inference and lower latency with models specifically tuned for production environments.
Performance Comparison
| Metric | Standard LLM | TensorCortex Distilled | Improvement |
|---|---|---|---|
| Model Size | 7GB | 2.1GB | -70% |
| Inference Speed | 100ms | 32ms | 3.1x faster |
| Memory Usage | 16GB | 4.8GB | -70% |
| Benchmark Accuracy | 76.4% | 74.8% | -1.6% |
* Results shown are averages across multiple model types and sizes. Your specific results may vary.
How We Transform Models
We've developed a comprehensive process that ensures your models are optimized for maximum efficiency without compromising on the capabilities that matter most.
Analyze
We analyze your model and requirements to understand your specific needs and constraints.
- Model architecture review
- Performance requirements analysis
- Use-case specific capability mapping
- Deployment environment assessment
Distill
Our specialized techniques distill knowledge from large models to smaller, more efficient ones.
- Knowledge distillation techniques
- Task-specific optimization
- Hyperparameter tuning
- Quantization & pruning strategies
Optimize
We fine-tune the distilled model to ensure it meets or exceeds performance requirements.
- Hardware-specific optimization
- Inference latency reduction
- Memory footprint minimization
- Runtime environment adaptation
Ready to optimize your LLMs?
Join our pioneer program today and experience the power of our advanced model distillation technology.
Get Early AccessWhat's Next for Tensor Cortex
Our roadmap is focused on making advanced model distillation accessible to more organizations through self-service tools and expanded capabilities.
Q2 2025
Self-Service Distillation Platform
Launch of our web-based platform allowing users to upload models and configure distillation parameters through an intuitive interface.
- User-friendly web interface
- Automated distillation workflows
- Performance benchmarking tools
- Domain-specific optimization techniques
- Multi-modal model support
- Advanced pruning algorithms
Q3 2025
Advanced Optimization Techniques
Expansion of our distillation capabilities with new techniques for specialized domains and multi-modal models.
Q4 2025
Template Library & API
Launch of pre-configured templates for common use cases and a comprehensive API for seamless integration with your workflows.
- Industry-specific model templates
- RESTful API for programmatic access
- CI/CD integration options
Get early access and help shape our roadmap
Get Early Access Today
Join our exclusive pioneer program and be among the first to leverage our distillation technology for your own models and applications.
Early Adopter Benefits
Receive dedicated technical support and preferred pricing as a pioneer partner.
Custom Optimization
We'll work directly with your team to optimize models for your specific use cases.
Priority Access
Be first in line for new features and capabilities as they're developed.
Limited spots available. Pioneers will be selected based on use case fit.