Own your AI — don't just rent it.
We design, train, and operate end-to-end LLM systems on your infrastructure. From GPU clusters to retrieval pipelines, your AI capability stays yours — fast, governed, and observable.
End-to-end AI engineering
Models need pipelines, GPUs, observability, and security controls — just like any production system. We build both sides.
Custom LLM Development
Pre-training, continued pre-training, and fine-tuning on your data. Open-weight models you can audit, deploy, and own.
GPU Infrastructure
Provisioning, scheduling, and cost control for AI workloads across NVIDIA H100/A100 clusters — cloud, on-prem, or hybrid.
RAG & Retrieval
Vector stores, hybrid search, and governed retrieval pipelines. Accuracy, freshness, and access control by design.
Inference Serving
vLLM, TensorRT, and Triton-based serving with batching, quantization, and autoscaling for cost-efficient throughput.
Evaluation & Observability
Offline evals, online tracing, and drift detection so production AI behaves predictably under real load.
Agents & Tooling
Agentic workflows with tool use, structured outputs, and human-in-the-loop guardrails for production reliability.
Use cases we ship
Domain-Specific Assistants
Customer support, internal knowledge, and specialist tooling — grounded in your data, not the open internet.
Document Intelligence
Extraction, classification, and summarization across contracts, claims, and operational documents at scale.
Search & Discovery
Semantic search and RAG-powered discovery layered on existing data stores — without rewriting your stack.
Bring your hardest AI problem.
We'll scope a proof-of-concept, set the eval bar, and tell you honestly whether AI is the right tool — before any infrastructure is built.