Software engineering. Applied AI.

Applied AI / For business and enterprise teams

Make AI useful.
In your operation.

Improve AI already in use or build a capability your existing tools cannot deliver on their own. Form From connects models, information and software around the work your team needs to complete.

Four graphite-green components joined into one sculptural assembly.

Where we can help

Bring us the part
that isn’t working yet.

A pilot has stalled

The demonstration works, but everyday tasks expose unreliable answers, missing context or too much manual correction. Establish what needs to change before extending it.

The work crosses systems

Connect records, checks and actions across your existing software. Carry permissions through the workflow and make exceptions visible to the people responsible.

A product needs to do more

Let users describe a task and have the application help complete it. Engineer the supported actions, approval steps and checks on what actually changed.

Selected work

Experience inside real workflows.

Explore the portfolio

The engineering around AI

Fit the system
to the responsibility.

Established AI products can cover a useful part of the task. We assess what your current tools support, engineer the missing connections and verify the result in the environment where the work happens.

Your data and obligations

Map processing, retention and provider access. Carry staff and client permissions into retrieval and connected tools, and agree the evidence your privacy and security owners need.

Authority to act

Define which actions can run automatically, which require approval and how incomplete work reaches a person. Record the source, decision and resulting action where the workflow needs it.

Quality and operating cost

Compare models against representative work. Assess response time, retries, review effort and cost per accepted result. Consider open-weight options alongside managed services.

Australian processing and hosting are available. We can also scope work in your own cloud or on premises, with the deployment and operating responsibilities agreed for the system.

Read the technical approach

Explore the possibilities

What could that look like?

Open an example to see what the system could do and how we would assess it.

01 / Commercial / Tender responsesCan we reuse our best tender answers without exposing another client’s terms?

The task

The bid team has relevant material spread across previous submissions, project records and capability statements.

What could improve

Spend less effort finding material and more on a proposal that fits the opportunity.

How it could work

Bring approved evidence into a source-linked first draft and flag questions the available material cannot answer.

What needs to be controlled

Respect project access and exclude client-specific commercial terms. The bid owner checks claims and approves submission.

What we would test

Can the reviewer trace each claim? Does restricted material stay out of the response?

02 / Operations / Supplier onboardingCan the system move a supplier through onboarding and flag what needs attention?

The task

Procurement reconciles forms, insurance records and internal approvals before setting up a supplier.

What could improve

Reduce manual coordination while keeping ownership of supplier approval.

How it could work

Check the pack, request missing information through an agreed workflow and route a complete record for approval. Update the supplier system only once authorised.

What needs to be controlled

Define which steps can run automatically. Keep supplier approval with an authorised person and record the evidence behind each update.

What we would test

Do missing approvals or expired documents stop activation? Can the team follow the record of each action?

03 / Product / AI in an existing applicationCan customers complete a task in our product by describing what they need?

The task

Users know the result they want but have to navigate several screens and repeat steps to get there.

What could improve

Make an existing product easier to use, with control over the actions AI can take.

How it could work

Connect natural-language requests to supported product actions. Check the result in the application and show the user what changed.

What needs to be controlled

Apply the user’s existing permissions. Require confirmation for consequential changes and make failed or incomplete actions visible.

What we would test

Does the requested change actually happen? Can the system recover or escalate when it cannot complete the task?

Illustrative scenarios, not measured client results.

A starting point

Establish what the next
decision needs.

A first conversation helps identify the question. A working session can align the people involved; a technical assessment can examine an existing system; a feasibility test can resolve an uncertain approach. When the scope is already clear, we can begin with engineering.

Let’s make it work

What needs to work better?

Tell us what happens today, where it falls short and which systems are involved. You do not need to select a model or write a specification first.

Start a conversation