Dweve Core: Complete AI framework that runs on any hardware
Most AI is frustratingly slow and expensive. Dweve Core changes that: one complete framework with an easy DSL for building any model, training and inference engines, and thousands of optimised algorithms. Runs fast on any computer, no GPU required.
We get your frustration
Current AI is painfully slow, expensive, and requires juggling a dozen different tools just to get something working. You shouldn't need a PhD and a massive budget to build useful AI.
Waiting forever
Traditional AI models take forever to respond, making real-time applications basically impossible unless you have massive computing power.
Crushing costs
API costs spiral out of control as you scale, and running your own models requires expensive GPUs that most businesses simply cannot afford.
Hardware mismatches
AI models are designed for specialised, expensive hardware that you probably don't have. Your existing servers and computers can't run them efficiently.
One framework to replace them all
Stop juggling PyTorch, TensorFlow, NumPy, and CUDA. Dweve Core is one complete framework: an easy DSL for building any model, thousands of algorithms, training and inference engines, and optimised kernels for every backend. Lowbit focus means fast, efficient AI on any hardware.
How Dweve Core works
Energy-efficient inference
Our binary quantisation makes AI run 10-100x faster while using a fraction of the memory and power. CPU inference that needs no GPU.
- • Works on standard servers
- • No expensive GPUs required
- • Dramatically lower costs
- • Deploy anywhere
Enterprise performance
Get professional-grade AI performance on your existing hardware infrastructure.
- • Efficient responses
- • Handle complex workloads
- • Scale effortlessly
- • Proven reliability
No compromise quality
Maintain exceptional accuracy while gaining massive efficiency improvements.
- • High-quality results
- • Consistent performance
- • Production-ready
- • Industry-tested
Model compression that makes AI fit anywhere
Tiny model weights
Smart data handling
Memory tricks
Real-world performance, no GPU required
Binary neural networks don't just work in theory. They deliver dramatic improvements with CPU inference on the hardware you already have. No GPU required.
CPU inference performance
On standard business hardware, no GPU required
Real-world results
Massive AI model running on standard servers
Why this matters to you
CPU inference on your hardware
Professional results
Practical benefits
Model compression delivers massive memory savings
Dramatically lower power usage
Binary neural network training
We've developed proven techniques to train highly efficient binary neural networks. Our approach combines expert knowledge transfer from larger models with smart optimisation strategies that work reliably at scale.
Training efficiency
Training methodologies
Advanced gradient techniques
- • Multiple training approaches for different precision levels
- • Smart techniques to maintain quality whilst reducing size
- • Proven methods for stable, reliable training
Knowledge distillation
- • Multiple distillation strategies for model training
- • Transfer knowledge across precision levels
- • Self-improvement and ensemble techniques
Distributed and specialised training
- • Efficient distributed training across multiple servers
- • Specialized methods for edge devices and privacy
- • Memory-efficient techniques for large models
Build anything
One framework for every AI application - from tiny edge models to massive enterprise systems, all on the hardware you already have.
Model development
Build and train any model with an easy DSL and powerful training engine
Design any neural architecture with our intuitive DSL. Train with built-in engine, backtest your models, deploy anywhere. Full bit-width support from binary to bfloat64.
Edge to cloud deployment
Same codebase runs everywhere - from microcontrollers to data centres
Deploy the same model to edge devices, servers, browsers, or GPUs. Optimised kernels for every platform mean you write once and run fast everywhere.
Industry applications
Manufacturing and IoT
- Vision models on factory edge devices
- Real-time inference on standard CPUs
- Runs on existing hardware
Retail and finance
- Recommendation systems on commodity hardware
- Real-time fraud detection at scale
- Low-latency inference for trading
Healthcare and security
- Medical imaging on hospital infrastructure
- Privacy-preserving on-device inference
- Threat detection without cloud dependency
Let's have a real chat
No sales robots, no automated responses: just real European AI experts who understand your challenges and actually want to help you succeed.
Ready to talk?
Whether you want to explore the technology, discuss a specific use case, or join our selective onboarding program, we're here to help.