We architect resilient GPU compute clusters, optimize distributed training pipelines, and deploy autonomous agentic infrastructure built for low latency and deterministic execution at enterprise scale.
# Distributed Cluster Topology
NodeCount: 128 x H100 / Blackwell
Interconnect: 3.2 Tbps RoCEv2 / IB
Framework: Megatron-Core / Ray
# Serving Throughput
TTFT: 18.2ms (P99)
Throughput: 4,820 tok/s/instance
Architect 3D parallelism (Tensor, Pipeline, Data) pipelines. Maximize Model Flops Utilization (MFU), mitigate communication bottlenecks, and stabilize large checkpointing.
Deploy production inference engines with dynamic batching, PagedAttention, speculative decoding, and quantization (FP8/AWQ) for predictable P99 latency SLAs.
Design multi-agent orchestration, state persistence, tool-use protocols (Model Context Protocol), and structured guardrails for deterministic autonomous workflows.
Modern AI systems do not fail at the prompt level—they degrade under memory bandwidth constraints, unoptimized kernel operations, and poorly tuned networking layers. We bring deep systems profiling to bridge research prototypes into resilient, cost-effective infrastructure.
01. Profiling & Architecture Audit
Comprehensive audit of cluster utilization, memory leaks, latency percentiles, and infrastructure spend.
02. Infrastructure Deployment
Implementation of distributed runtimes (vLLM, Ray, TensorRT-LLM) and agent orchestration fabrics.
03. Scale & Knowledge Transfer
Load testing under peak throughput, stress testing failover nodes, and full technical documentation for in-house teams.
Whether you are optimizing multi-node model training runs or architecting enterprise-wide agent deployments, we provide expert systems consulting.