Your models.
Your metal. Your data.
Private LLM deployment and agent infrastructure on GPUs we own. Zero-egress inference means your prompts, documents and customer data never touch a third-party API.
0
bytes sent to third-party APIs
24 GB
dedicated GPU VRAM
<50ms
inference latency (8B-class)
$0
per-token API cost
Private LLM deployment
Ollama and vLLM serving on dedicated RTX 3090 hardware — OpenAI-compatible endpoints your apps already know how to call. Open-weight models (Qwen, Llama, Mistral, DeepSeek) sized to your latency and quality budget.
Fine-tuning & custom models
LoRA/QLoRA training pipelines (Soup, PEFT, TRL) on your documents, tickets, and domain knowledge. A small model trained on your data beats a giant model guessing at it.
Agents & RAG pipelines
Self-hosted agent runtimes wired to your tools — retrieval over your documents, structured tool-calling, memory. Built so you can inspect every call, not a black box.
Quantitative & trading systems
Latency-budgeted trading bots, prediction-market systems, and time-series forecasting — from data ingestion to execution, on infrastructure close to the wire.
Who this is for
- Companies with data that legally can't leave their control
- Products needing predictable, flat-cost AI at any volume
- Teams who've outgrown per-token pricing on API calls
- Anyone who wants to inspect, audit and own the whole stack
Want AI without the egress?
Tell us what you're trying to automate or build — we'll spec the model size, hardware path and a fixed monthly cost.