Agentic AI · NVIDIA Stack · Production Inference

We build agentic AI systems — and the inference factories that run them.

Westmind Ltd. is an AI engineering studio. We architect multi-agent systems, deploy them on NVIDIA-grade infrastructure, and operate the inference layer that keeps them running 24/7. From the first whiteboard sketch in Mermaid, to OpenClaw in development, to NemoClaw in production — one partner, full ownership.

Book a consultation → Explore agentic AI
Mermaid → OpenClaw → NemoClawAgentic pipeline
DGX B200 · H200 · BasePODNVIDIA-aligned
On-prem · Cloud · EdgeDeployment targets
// Stack we deploy and operate
NVIDIA AI Enterprise
OpenClaw
NemoClaw
NeMo Guardrails
TensorRT-LLM
Triton
PyTorch
TensorFlow
Hugging Face
Docker
Kubernetes
LangGraph
Ray
vLLM
// 01 — Services

One engineering team across the AI stack.

Architecture, software, models and inference under a single roof. We bring the disciplines required to ship an AI product to production — and to keep it there.

AI Architecture

System design for AI products: agent graphs, data flow, model selection, retrieval, evaluation, guardrails and cost modelling — translated into a concrete technical blueprint your team can execute.

// blueprints · evals · cost models

Development

Full-stack development of AI-native applications — backends, agentic workflows, RAG pipelines, fine-tuning loops, and user-facing interfaces — built to be observed, tested, and maintained.

// agents · pipelines · interfaces

Inference

We operate the runtime: GPU and CPU serving, quantisation, batching, autoscaling, monitoring, and SLA management — on cloud, on-prem, or at the edge. Predictable latency, predictable cost.

// serving · scaling · slas

Consultation

Advisory engagements for technical leaders: build-vs-buy decisions, vendor selection, AI readiness audits, and roadmaps that align model capability with business reality.

// audits · roadmaps · advisory

RAG & Knowledge

Retrieval systems over your proprietary data — indexed, evaluated, and tuned. We connect models to the documents, databases, and tools your teams actually rely on.

// retrieval · indexing · evals

Custom Models

Fine-tuning, distillation, and small-model deployment — when off-the-shelf APIs aren't the right fit for cost, latency, privacy, or capability reasons.

// fine-tuning · distillation · slm
// 02 — Agentic AI

Multi-agent systems that operate in production.

We set up agentic AI working mechanisms for partner companies — from the first workflow sketch, to a supervisor-worker stack running behind enterprise guardrails. Three tools, one pipeline.

// 01 Design

Mermaid workflow design

Every engagement starts with a diagram. We translate business logic into agent graphs — supervisor, workers, tools, retries, guardrails — visualised in Mermaid before a line of code is written. The diagram is the contract.

// flow diagrams // review-ready // version-controlled
// 02 Implement

OpenClaw orchestration

We build the system on OpenClaw — the open-source multi-agent orchestration framework — with sandboxed execution per agent, tool integrations, and clean bridges to LangChain, LlamaIndex, and Semantic Kernel. Audit logs and per-agent YAML policies from day one.

// supervisor + workers // sandboxed exec // tool bridges
// 03 Harden

NemoClaw enterprise

For production we wrap it in NVIDIA NemoClaw: NeMo Guardrails on every input and output, native Nemotron models via NIM, GPU-optimised inference, and one-command install. Self-evolving agents, with the safety rails enterprise demands.

// nemo guardrails // nim-backed // gpu-tuned

Partner deployment — supervisor / worker pattern

Live · Mermaid graph
graph LR U(["User · Partner App"]) --> S{"Supervisor Agent"} S -->|decompose| W1["Research Worker"] S -->|decompose| W2["Code Worker"] S -->|decompose| W3["Data Worker"] W1 --> T1[("Web · APIs")] W2 --> T2[("Repo · CI")] W3 --> T3[("DB · Warehouse")] T1 --> G{{"NemoClaw Guardrails"}} T2 --> G T3 --> G G --> N["NIM · Nemotron Inference"] N --> R(["Response · Audited"])
// 03 — Capabilities

The stack we work in, every day.

Stack-agnostic in principle, opinionated in practice. These are the areas where we ship fastest and most reliably.

Live · Inference Graph
// 04 — Process

How an engagement unfolds.

A short, structured path from the first conversation to a running system in production.

// 01

Discovery

We map the problem, the data, the constraints, and what "good" looks like — measurably.

// 02

Architecture

Mermaid diagrams, model choices, evaluation plan, GPU sizing and cost envelope — written down.

// 03

Build

Iterative development on OpenClaw with weekly demos. Evaluations gate every milestone, not vibes.

// 04

Operate

NemoClaw-wrapped deployment on NVIDIA hardware. We run it — or hand off cleanly to your team.

// 05 — Get in touch

Have an AI problem worth solving?

Tell us about it. We reply to every serious inquiry within two working days, usually with questions of our own.