Service

Agentic Workflows

Multi-step processes that run themselves. AI handles the decisions. Automation handles the execution.

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What this covers

LLM-in-the-loop automation

Workflows where an LLM handles the judgment calls — classification, extraction, routing, summarisation — while deterministic code handles everything else.

n8n and Windmill orchestration

Visual and code-based workflow orchestration. n8n for integrations-heavy flows, Windmill for code-first pipelines that need Git, versioning, and proper deployment.

Trigger-based pipelines

Workflows that fire on events: new email, Slack message, form submission, webhook, cron schedule. No manual kicking-off required.

Human handoff points

Not everything should run fully autonomously. I design workflows with clear escalation paths — where the AI handles it, and where a human needs to review.

Built withn8nWindmillZapierLangChainCrewAIClaude APIDockerWebhooks

How it works

01

Audit the current process

Walk me through what happens today — the tools, the handoffs, the friction. I map it and identify where automation earns its keep versus where it creates fragility.

02

Design the agentic layer

Which steps need an LLM. Which need a tool call. Which need a human. The workflow is designed before a single line is written.

03

Build, connect, run

Workflow built in n8n, Windmill, or code-native depending on requirements. Integrated with your existing stack. Monitored from day one.

Enterprise context

Wesfarmers / CM3AI transformation at enterprise scale — agentic processes embedded across operations, not bolted on as a prototype.
Employment

The same rigour applies whether the workflow handles 10 records a day or 10,000.

What are your team's
most repetitive decisions?

Those are the ones worth automating first.

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