Services
Audit, build, then keep it running.
Each step is priced before it starts, and you can stop after any of them.
01
Audit
- Price
- A$2,500 to A$3,500 plus GST
- Fixed before we start. Credited in full against the build if you go ahead within 60 days.
- Timeframe
- Two to three weeks
We get into your systems, process and people to find the one workflow worth automating first, and give you a fixed price to build it.
This is a working audit, not a survey. We look at the systems themselves, so that the build price can be fixed and the automation fits your security and privacy obligations from the start.
What we do
- Walk the workflow with the people who do it, and measure where the time goes.
- Review the systems involved: applications, integrations, data, and code where there is any.
- Review your cloud environment and security settings for what an automation would need.
- Identify where privacy and record-keeping rules are likely to apply, including the changes that start on 10 December 2026, so your advisers can confirm them.
What you get
- A short written report: what we found, the workflow to start with, and the hours it should give back.
- A fixed price, plan and timeframe for the build.
- The risks, and the controls we would put in place for each.
What we need from you: A sponsor, a few hours with the people who run the process, and read access to the systems involved.
02
Build
- Price
- Fixed price, set in the audit
- Timeframe
- Usually four to eight weeks for a first workflow
We build that workflow inside your own cloud, using AI only where it does a job that ordinary automation cannot.
Most of what slows a team down can be fixed with plain automation: rules, integrations and well-built workflows. We add AI only where it earns its place, such as reading unstructured documents or drafting text for a person to check. Both are built to the principles of ISO/IEC 27001 for information security and ISO/IEC 42001 for AI management, fitted to your own policies rather than ours.
What we do
- Start with the simplest thing that works. Rules and integrations come first; AI is used only where the task needs judgement over unstructured information.
- Build in your Azure, AWS or Google Cloud account, connected only to the systems the workflow needs, with access limited to what each step requires.
- Where AI is used, record what it is for, what data it sees, how it was tested and who checks its output.
- Treat the automation like any other system you run: change control, logging and access reviews under your security framework.
- Test it against real examples before go-live, and keep a person approving anything that matters.
What you get
- The working automation in production, running in your environment.
- The documents your security team and auditors will ask for: what it does, what it can reach, how it was tested and who is accountable.
- A handover session for the people who will run it, and a period of support after go-live, set out in the quote.
03
Run and advise
- Price
- Monthly, agreed up front
- Timeframe
- Month to month
We keep it running, add the next workflow, and give you senior technology advice when you need it.
Once it is running, we keep it running and help you decide what comes next. You can stop at any time.
What we do
- Monitor the automation, and fix or update it as your systems and the AI services change.
- Scope and price the next workflow the same way as the first.
- Give senior advice when you need it: security reviews, tenders, board papers and vendor decisions.
What you get
- Someone accountable for the automation after go-live.
- Access to experience across the CTO, CIO and CISO roles, for as much or as little as you need.
Common questions
- Which clouds do you work with?
- Microsoft Azure, Amazon Web Services and Google Cloud. Most of our work is on Azure and Microsoft 365.
- Where does our data go?
- It stays in your environment. We use the enterprise AI services in your own cloud account, such as Azure OpenAI, Amazon Bedrock or Google Vertex AI. Under those services’ enterprise terms, your data is not used to train their models.
- Who owns what you build?
- You do. The output lives and runs in your environment.
- What if the audit finds nothing worth automating?
- Then the report says so, and you keep it. A clear no is a useful answer and costs far less than a build that should not have happened.
- How is TAGD connected to Cordexa?
- Dave Tormey founded both. Cordexa is a software platform for document-heavy expert work, and TAGD is the consulting practice. We only suggest Cordexa when it fits the work better than a custom build.
Tell us about the work that takes the time.
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