AI workflow automation for documents, extraction and classification
AI that reads and sorts the information your team currently handles by hand.
AI workflow automation puts a model inside one step of a process you already run: reading a document, extracting fields, or classifying an enquiry. The rest of the workflow stays ordinary, and a person keeps the checks that matter. We suggest it only when that step needs it.
Who this is for
Teams that already have a process, and one step in it that depends on a person reading. 23Labs is a software and automation company based in Melbourne. We work remotely with businesses across Australia and New Zealand, and we do not add AI where a rule would do.
The input is a document or an email
Invoices, rate requests, CVs, applications or client documents arrive as PDFs or free text, and someone turns them into fields before anything else can happen.
Staff time goes on sorting
People read and classify incoming enquiries so the right workflow can start. The decision after that may still belong to a person.
A fixed rule was considered and does not fit
The step cannot be written as 'if this field equals that'. If it can, business process automation is the simpler service.
The reading this is meant to take on
The bottleneck is interpretation. Someone has to understand unstructured information before a process that is otherwise familiar can continue.
Details buried in documents
The fields a job, an invoice or an onboarding record needs are sitting in a PDF, a scan or an attachment, not in a form.
Enquiries that are not a category yet
An email or a message has to be read before anyone knows which team, which job or which template applies.
Every item waits on a person
Nothing downstream moves until someone has interpreted the input, so volume shows up as delay rather than as a queue the system can see.
Where AI earns a place in the workflow
We use AI for the interpretive step only: document processing, data extraction and classification. The result is written back into the process your team already runs. We do not rebuild the surrounding handoffs as an AI project.
When this is the right service
Use this when a person currently reads something before the process can move. Copying a known field, sending a reminder or creating a task from a form is business process automation, and it does not need a model. An AI agent is different again: it carries out a task across systems, with limits and approval, rather than extracting or classifying one input. If the business needs a new place for the work to live, that is custom software.
How an AI workflow engagement works
We start from the step, not from a model. If we cannot point at information a person has to interpret, we will say so and recommend a simpler automation.
Find the interpretive step
We look for the point where someone reads a document, an email or a free-text enquiry and turns it into structured information.
Define the output and the check
We agree the fields or the classification, and which results a person still reviews before they move on.
Put that step in the existing process
The model reads the input and writes the result into the workflow. The surrounding handoffs stay ordinary automation.
Compare it with how a person handles the same items
We review real outputs, tighten the instructions, and only then let it take a place in the live process. Items you mark as sensitive keep a person in the check.
Where a model actually helps
These are examples of the step, in transport and logistics, recruitment, and professional services. None of them is a completed AI project. There is no AI workflow case study on this site yet.
A rate request or a proof-of-delivery document arrives as a PDF or an email, and someone reads it before a job record can be updated. The AI step is that reading. Creating the job from fields that are already structured does not need a model.
A CV or an application arrives as unstructured text and someone classifies it against an open role before a recruiter decides. That classification is the workflow step. An agent that corresponds with the candidate is a different service.
An enquiry or a pack of client documents has to be read so onboarding fields exist. The extraction is the AI step. The reminders and task creation around it are ordinary process automation.
Published work, and what it is not
Nothing published on this site is an AI workflow. The projects below are process and integration work. Where the step already followed a rule, that is what we built. AI would have been the wrong recommendation.
CorIT Tech
Client onboarding was a manual transfer from the CRM into project records. The fix was a workflow that creates the projects and tasks from information the CRM already held. CorIT reported saving more than 10 hours of administrative work a month. No model was required.
Read the projectAustralian real estate office
Enquiries needed to reach the property record and the right person. That was a website improvement and a set of workflow triggers, not document classification.
Read the projectFrequently asked questions
What is AI workflow automation?
It is using AI inside a defined business process for a step that needs reading or judgement: pulling fields out of a document, classifying an incoming email, or sorting unstructured information so a person can act on it. The rest of the workflow stays a normal process.
When should we avoid AI?
When the step already follows a fixed rule. Copying a field from one system to another, sending a reminder, or creating a task from a form does not need a model. That is business process automation, and it is usually simpler to run.
How is this different from an AI agent?
An AI workflow step does one job inside a process you already own, such as extracting invoice lines or classifying an enquiry, and hands the result on. An AI agent is built to carry out a task that may involve several lookups and actions, within limits you set.
Do you have a published AI case study?
No. The published projects are process automation, system integration and a website rebuild. We will only propose AI when your workflow has a step that rules cannot handle.
How much does AI workflow automation cost?
Custom software and automation projects typically start from A$2,500. Final pricing depends on the systems involved, complexity and scope. For a larger or more complex project, book an initial consultation. It also depends on the step, how much a person still needs to review, and which system the result has to land in. We do not quote a model licence or a package rate on this page.
Do you work with New Zealand businesses?
Yes. The work is delivered remotely from Melbourne for clients in Australia and New Zealand. There is no New Zealand office.
Show us the step someone still has to read.
Describe the document, email or enquiry that has to be interpreted before the process can move. If that step is already a fixed rule, we will say so and treat it as process automation.
Custom software and automation projects typically start from A$2,500. Final pricing depends on the systems involved, complexity and scope. For a larger or more complex project, book an initial consultation.