Model Infrastructure
Scalable serving, continuous evaluation, and fine-tuning for custom foundation models.
ML Lifecycle
We implement CI/CD for ML models, enabling automated evaluation, red-teaming, and zero-downtime deployments.
High-throughput inference serving using vLLM and TensorRT-LLM.
Automated continuous evaluation and bias testing pipelines.
LoRA/QLoRA fine-tuning workflows on scalable GPU clusters.
Why it matters for Production.
Cost Optimization
Replace massive, expensive public LLMs with highly-tuned, cost-effective SLMs.
Low Latency
Optimized inference engines dramatically reduce Time-to-First-Token (TTFT).
Predictable Releases
Rigorous ML CI/CD ensures new model weights are tested before hitting production.
Stop guessing.
Start shipping.
Thirty minutes with a senior engineer. No sales deck, no junior SDRs. Just a technical conversation about what's actually breaking or slowing you down.