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AI AGENTS · AUSTRALIA

Give AI a job.
And a way to do it.

We design, connect and test AI agents for Australian businesses: a defined task, approved information, permitted tools, human review and a documented handover.

Plan your first agent

What we mean by an AI agent: software that uses a model and connected tools to work through a task. The useful part is the whole system: its instructions, data access, actions, checks and the way people take over.

Claude Partner Network member

ONE POSSIBLE WORKFLOW

From a request
to a reviewed action.

Illustrative enquiry workflow. Your sources, actions and approval points are defined around your business.

  1. 01 / RECEIVE

    A request arrives.

    A form or internal task supplies the starting information.

  2. 02 / CHECK

    Use approved sources.

    Retrieve the relevant records and flag missing details.

  3. 03 / PREPARE

    Draft the next step.

    Prepare a response or proposed record update with its context.

  4. 04 / APPROVE

    A person decides.

    Review the proposal before an agreed external action runs.

WHAT YOU CAN COMMISSION

The agent.
The connections.
The controls.

We scope the work around a useful task. These are the delivery decisions we make explicit before the build.

Discuss your agent
  1. 01

    Task and success criteria

    Define the users, starting inputs, permitted outputs and examples that demonstrate a useful result.

  2. 02

    Tool and knowledge connections

    Connect the agreed systems and approved information. Document access boundaries and what the agent must not do.

  3. 03

    Human approval and exception handling

    Set review points, failure behaviour and a clear path back to a person when information is missing or an action is outside scope.

  4. 04

    Evaluation before release

    Check representative examples, edge cases, output quality and tool actions against the agreed acceptance criteria.

  5. 05

    Release and handover

    Agree deployment, logging, running costs, ownership, documentation and the responsibilities for ongoing operation.

START WITH THE TASK

Where an agent
could help.

Examples of tasks we can scope around your systems, information and review process.

OPERATIONS

Prepare incoming work.

Read a request, assemble the relevant records and prepare a reviewable task for your team.

KNOWLEDGE

Find an answer with context.

Search approved documents and put the supporting sources beside a draft answer.

RESEARCH

Build a usable brief.

Gather permitted information, organise the findings and flag gaps for a reviewer.

BEFORE WE BEGIN

Questions about AI agents.

Do we need an agent or a simpler automation?

An agent can help when the next step depends on what it finds. If the process is predictable, a fixed workflow or integration may be easier to test and operate. We assess the task before choosing the implementation.

Can you set up Claude for our team?

Yes. Our AI workflow offer includes practical Claude adoption workshops and implementation around your team’s work. DataXLR8 is a Claude Partner Network member. Tool access, provider settings and subscriptions are agreed in scope.

How do we decide whether the agent is good enough?

Bring real, appropriately shared examples and define acceptable results. We agree evaluation cases and review both the output and the actions taken. Unclear requests and failures are part of the review, not just ideal examples.

Will it send messages or change records automatically?

Only the actions and approval rules agreed for the engagement should be enabled. We do not assume that an agent may send external communications or make consequential changes without review.

What does AI agent development cost?

Fixed-price quotes. Most projects start from AUD $5,000, and small jobs are welcome. The number of tools, data readiness, evaluation requirements and deployment environment affect the quote. Model usage, subscriptions and ongoing support are identified separately.

What happens when a model or connected tool changes?

The operating plan should identify who monitors failures, checks changes and maintains the evaluation examples. Ongoing operation and improvement can be scoped as a separate managed service.

LOOK AT THE WORK

See the engineering.
Meet the people.

Our public products let you inspect the interface and its sources. Our delivery experience and owned projects are explained separately.

Try our public data products Read our Data Lab case study Plan an AI consulting engagement Read the delivery experience Meet our founder

YOUR NEXT STEP

Start with one useful agent.

Tell us the task, the tools it needs and what a good result looks like.

Start the conversation

Fixed-price quotes. Most projects start from AUD $5,000, and small jobs are welcome.