CompactifAI
The AI model compressor to make AI systems faster, cheaper and energy efficient.
Have your AI model compressed and benefit from efficient and portable models. Greatly reducing the requirements for memory and diskspace, making AI projects much more affordable to implement.
Meta Models
Mistral Models
DeepSeek Models
DeepSeek R1 Slim
Cost Savings
Lower your energy bills and reduce hardware expenses.
Privacy
Keep your data safe with localized AI models that don't rely on cloud-based systems.
Speed
Overcome hardware limitations and accelerate your AI-driven projects.
Sustainability
Contribute to a greener planet by cutting down on energy consumption.
Current AI models face significant inefficiencies, with parameter counts growing exponentially but accuracy only improving linearly.
This imbalance leads to:
Skyrocketing Computing Power Demands
The computational resources required are growing at an unsustainable rate.
Soaring Energy Costs
Increased energy consumption not only impacts the bottom line but also raises environmental concerns.
Limited Chip Supply
The scarcity of advanced chips limits innovation and business growth.
Revolutionizing AI Efficiency and Portability: CompactifAI leverages advanced tensor
networks to compress foundational AI models, including large language models (LLMs).
This innovative approach offers several key benefits:
Enhanced efficiency
Drastically reduces the computational power required for AI operations.
Specialized AI models
Enables the development and deployment of smaller, specialized AI models locally, ensuring efficient and task-specific solutions.
Privacy and Governance Requirements
Supports the development of private and secure environments, crucial to ensure ethical, legal, and safe use of AI technologies.
Portability
Compress the model and put it on any device.
Size Reduction
Parameter Reduction
Faster Inference
Faster Retraining
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Ready to transform your AI Capabilities?
Contact us today to learn how CompactifAI can streamline your AI operations and drive your business forward.