Applied AI & Custom Machine Learning Inference Engines.
How does CPSS develop and deploy custom machine learning models?
CPSS develops proprietary machine learning models tailored to specialized enterprise datasets. We engineer custom neural architectures, fine-tuned transformer models, and real-time predictive analytics pipelines, optimizing weights for hyper-efficient edge and cloud inference while maintaining strict data sovereignty and full algorithmic transparency without external vendor lock-in.
Tensor Inference & Latency Benchmarks
ON-PREMISES GPU INFERENCE BENCHMARKS
Sovereign AI Engine Specifications
Designed to provide complete intellectual property ownership over model weights, training data, and inference pipelines.
Hardware-Accelerated Tensor Pipelines
Direct GPU kernel optimization compiling custom PyTorch/JAX models into low-latency TensorRT runtimes with dynamic batching and unified memory management.
Self-Hosted Vector Retrieval & Sovereign RAG
High-density HNSW vector search architectures integrated with hybrid BM25 full-text indexing, delivering enterprise RAG with zero data leakage.
Fine-Tuned Domain Transformers & SLMs
Tailored domain adapter fine-tuning (LoRA/QLoRA) producing lightweight, highly accurate enterprise models that run efficiently on private hardware.