AI Solutions
DML (Deep Learning & Machine Learning)
Training, additional training (fine-tuning) and GPU-inference of models for narrow industry tasks, computer vision and predictive analytics.
- 96%+
- F1-score accuracy of custom models
- 4x
- Accelerating inference through quantization
- 99.9%
- Uptime of high-load ML pipelines
Are you facing these issues?
High cost and latency of inference of heavy models
Running raw neural networks requires enormous GPU computing resources, making scaling uneconomical.
Solution
We optimize model weights using quantization methods (INT8/INT4), pruning and deploy them through high-performance vLLM and TensorRT engines.
Lack of labeled data for custom tasks
Boxed AI services do not understand highly specialized scripts, and manual marking of millions of samples is too expensive.
Solution
We use LoRA/QLoRA advanced training techniques, synthetic data generation and semi-automatic dataset validation pipelines.