A Decade of AI Infrastructure Evolution
From machine learning pipelines to enterprise AI orchestration, we've been solving real infrastructure challenges since the 2010s - helping you focus on building the future with AI.
Sherpa
Our first generation platform for ML model management, testing, validation and retraining. Built when "ML Ops" wasn't really a term yet.
Scout
Designed for the GenAI era, Scout helped organisations deploy their first LLMs on-premise with NVIDIA Ada GPUs and EPYC servers.
Olla
Open-source Inference proxy bringing enterprise patterns to the community. Unified interface for Ollama, LM Studio, vLLM, sglang, llama.cpp & others, with our learnings from Scout & Sherpa.
FoundryOS
The culmination of our experience. Enterprise AI LLM Inference platform with first class support for vLLM, SGLang & LlamaCpp with model unification, load balancing, health & monitoring and more.
What We've Learned
Real-world experience matters. We've worked across inference, training and infrastructure - building the tools that help engineers run AI at scale.
Performance is non-negotiable. Sub-5ms latency isn't marketing - it's what production systems demand.
Unification beats fragmentation. One platform for all your AI backends saves months of integration work.
Privacy drives adoption. Enterprises need their AI on their infrastructure, not in someone else's cloud.