AI agents · Production-grade

Agentic Workflows Developers in Australia.

AI agents that take action, not just answer questions.

Agents are what happens when LLMs stop being chat boxes and start doing work. We connect you with Australian developers who ship multi-step agents that plan, use tools, and finish real tasks (researched, refunded, scheduled, drafted, deployed) without a human in every loop.

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Timeline

2 to 16 weeks

Team

1 AI engineer, 1 backend dev

Starting from

from $5k

Best fit

Who this works for.

Operations teams whose work is repetitive but requires reasoning
Customer service agents that need to actually take action: refunds, lookups, rescheduling
Research, drafting, and analysis work currently eating senior staff hours

What's included

Every Australian engagement comes with these foundations.

Use-case scoping

Not every problem needs an agent. We test the use case against simpler approaches before committing to multi-step orchestration.

Tool integration

Function-calling against your real systems (CRM, billing, data warehouse, internal APIs) with proper auth and audit logging.

Planning and orchestration

Multi-step plans, retries, fallbacks, branching. Built on LangChain, CrewAI, or hand-rolled, whichever fits.

Evals and observability

Test sets, regression checks, full conversation traces. So you can tell a prompt change from a bug.

Human-in-the-loop guardrails

Every action above a risk threshold pauses for human approval. No agent goes rogue on production data.

Process

How a agentic workflows engagement actually runs.

Pilot

A 2 to 3 week scoped agent on one use case, with evals from day one. Go/no-go before any production commitment.

Production hardening

Tool sandboxing, rate limits, cost ceilings, audit logs, kill switches. Boring infrastructure that decides whether the agent ships or doesn't.

Phased rollout

Internal pilot → low-risk customers → full deployment. Each phase gates on evals and real-world metrics.

Operate and tune

Monthly review of accuracy, cost, escalation rate. Continuous prompt and tool refinement.

What you walk away with

Deliverables.

Production agent integrated into your stack
Eval suite with regression tests
Tool-use audit log
Cost and latency dashboard
Runbook for failure modes
Human-approval queue

Stack

Tools we use.

Anthropic Claude OpenAI LangChain CrewAI Pinecone PostgreSQL + pgvector LangSmith Temporal

We're stack-flexible. If your team already runs on something different, we'll match it.

Australian pricing

Three engagement sizes. One fixed price for each.

Quotes from three matched Australian developers come with their own pricing in AUD. These ranges are what most projects land on.

Pilot

from $5k

Scoped agent on one use case, with evals. Two to three weeks. Designed to prove value before production commitment.

1 use case
Eval harness
Internal pilot only
Go/no-go report

Most picked

Production

from $18k

Production-ready agent with tool integrations, guardrails, and observability.

Multi-step orchestration
Tool integrations
Guardrails + human-in-the-loop
8 to 12 week build

Platform

from $45k

Multi-agent system with shared tooling, evals, and orchestration. For teams running several agents in parallel.

Multiple agents
Shared tool registry
Centralised evals
Embedded team

FAQ

Common questions.

A chatbot answers questions. An agent takes actions: looks something up, refunds a payment, books a meeting, files a ticket. The boundary is whether the LLM produces words or causes side-effects.

Possibly, which is why production agents have guardrails: tool sandboxing, cost limits, human approval for risky actions, audit logs. Done right, the agent has a smaller blast radius than your most junior staff member.

We're model-agnostic. Anthropic Claude has the best tool-use behaviour in 2026 for most agentic patterns; GPT and Gemini work too. We pick based on cost, latency, and your data residency needs.

Fast. We architect the agent so models can be swapped without rewriting the surrounding code. The tools and evals matter more than the model choice.

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