CofatAI provides high-throughput inference engines and domain-specialized model orchestration optimized for distributed CUDA environments and enterprise SLAs.
Leverages advanced tensor quantization algorithms to shrink inference memory envelopes without loss in output fidelity.
Hardware-aware request pipelining maximizes GPU saturation, driving continuous sub-millisecond execution times.
Zero data retention guarantee. Deployable across on-premises clusters, hybrid clouds, or isolated sovereign VPCs.
Engineered directly on optimized runtime layers—including TensorRT-LLM and Triton architecture patterns—allowing CofatAI to deliver 5x cost reduction across enterprise inference operations.
$ cofat-bench --model cofat-enterprise-v1 --precision fp8
[INFO] Cluster: 8x H100 SXM5 80GB
[INFO] Compilation Target: CUDA 12.x / TensorRT-LLM
Running batch size 128 stress matrix...
Latency (TTFT): 11.4ms [PASS]
Throughput: 4,820 tokens/sec/GPU [PASS]
# Deployment ready for enterprise production
Direct inquiries for enterprise cluster integration and pilot partnerships.