What AI workflow automation does
AI workflow automation joins a repeatable task to the documents, checks and people needed to complete it. For a tender, that could mean turning requirements into a checklist, finding supporting evidence and preparing sections for a bid manager to review.
We build only where a clearer process, better template or existing product falls short. We use tools such as Power Automate and Copilot Studio where they fit, usually within Microsoft 365 and SharePoint. The tool choice follows the task, the information available and the checks your team needs.
Who a custom workflow is for
A custom workflow is for a business with repeated document work, identifiable source material and someone responsible for approving the result. We work with Australian businesses of roughly 10 to 150 staff, particularly professional and technical firms.
AI document automation might help organise report evidence, compare a tender with approved company records or prepare client correspondence from verified notes. If the source documents are incomplete or contradictory, we identify that first. AI cannot supply a missing qualification, project record or technical judgement.
What you get with the build
You get one defined workflow with the evidence, tests and documentation needed to judge whether it is fit for use. Scope and a fixed fee are agreed in writing before starting.
- A workflow specification covering the trigger, inputs, outputs, responsible staff and approval points.
- A build in your systems, using approved documents and agreed access permissions.
- Source references for factual claims, with missing or conflicting evidence flagged for review.
- An agreed test set of past examples and known problems, with expected results and recorded findings.
- A review checklist, instructions for failed or incomplete runs and a manual way to finish the work.
- Staff training and handover of the configuration, instructions, test records and ownership responsibilities.
How the build works week by week
Set up and build typically takes two to six weeks after scope is agreed. If the task or value is unclear, an AI strategy review takes about two weeks first. We agree the schedule around the work and access needed.
- 01Week 1: define the task and the testsWe map the existing process, select approved inputs and record current handling time. Your reviewer defines acceptable outputs and the errors that must be caught. We agree what the workflow must do when evidence is missing.
- 02Week 2: build a first version and test itWe build the agreed sequence and run it on approved examples. Your team checks sources, gaps and draft wording. We record failures and correct the workflow before anyone relies on its output.
- 03Weeks 3 to 6, where needed: refine and hand overFor a broader scope, we repeat the tests after changes and practise review with staff. We compare complete handling time with the starting position, document remaining limits and hand over when the agreed tests pass.
How we measure success
Success means the result meets agreed quality checks and takes less total effort, including human review. We measure preparation, checking and correction time, alongside missed issues, unsupported claims and false alarms, where correct work is flagged as a problem.
Capacity freed is the reduction in total time per item multiplied by the number handled. We report hours separately from cash savings. If reviewers spend the saved drafting time resolving errors, we need to correct the cause or narrow the scope before wider use.
What the tender review demo shows
Our tender review demo is an illustrative example built on invented data. It checked 52 requirements, found and ranked 18 issues, and drafted four response sections with a source behind every sentence.
The demo caught all 15 problems planted in advance, with zero false alarms. That result applies to the invented test set. For your workflow, we agree separate examples, the problems it must catch and who checks each output before use.
How we handle data and approval
We build in your systems and agree access, data handling and approval rules before starting. We use business-grade AI accounts that do not train on your data, offer a confidentiality agreement (NDA) and delete working copies at the end.
We confirm where information would be processed and flag personal information or client restrictions before testing. Your staff approve external correspondence and legal, commercial or technical claims. AI prepares the work; your authorised reviewer decides whether it is accurate and ready to use.
What we need from your team
We need a workflow owner, a reviewer and access to approved source material. Bring a typical completed example, a difficult one and examples of mistakes the process should catch. We also need your administrator's help with access and time from staff to test the build.