Baseline
Volume, effort, cycle time, leakage, exceptions and current cost.
AI operations for multi-site service businesses
Put one expensive workflow into production.
KNIC designs and deploys governed AI workflows across the systems you already use—with controlled actions, human exception handling, observable failure and results measured against an agreed baseline.
Best suited to a repeated workflow with at least $1 million a year in labour, delay, errors, vendor cost or revenue leakage.
The implementation problem
The model is rarely the hard part. The write path is.
Most organisations can generate AI ideas and demonstrations. Production work begins when a model must read live business context, decide inside explicit limits, change a system of record, recover from failure and leave an audit trail. KNIC builds that operating layer around one bounded workflow.
How the work gets done
Five controls between an idea and an operation.
Connect
APIs, databases, inboxes, documents and work tools already in place.
Control
Permissions, approval thresholds, action logs, rollback and alerts.
Route
A named person owns ambiguity, failure and high-consequence decisions.
Measure
Completion, intervention, error, cycle time and financial effect.
The first engagement
Start with a 10-day AI Workflow Diagnostic.
We select one material workflow and determine whether it deserves production investment. If the case does not survive operational and financial scrutiny, it stops there.
Implementation evidence
Proof, labelled honestly.
Owned-system build notes and synthetic demonstrations show implementation technique. They are not presented as client outcomes.
KNIC-owned system · verified build
One operating loop across Foxxkit, Bowerbird and Toucan Ops
How marketing, context and work are separated—and where human approval still gates publishing, sending and spend.
Read the build note →Synthetic demonstration
A controlled CRM write, deliberate failure and safe replay
Ambiguity fails closed, a dependency failure opens one owned exception, and idempotency prevents duplicate work.
Inspect the controls →Operator viewpoint
Designing for two species of user
Why software now serves people and agents at once, and what semantic structure and stable interfaces change.
Read the field note →Built by an operator
Production judgement before theatre.
Nathan Krisanski has spent more than 15 years building production software and data systems in Australian PropTech, including founding and exiting HomePrezzo. KNIC Ventures is his independent AI-operations implementation practice in Brisbane.
Where a diagnostic supports investment, KNIC offers a fixed $190,000 + GST production implementation for the agreed bounded workflow, normally delivered in six to eight weeks.
Nathan also serves as Head of Technology at The Agency Group Australia. KNIC is operationally and commercially separate. Employer or client work is never presented as KNIC evidence without written permission.
Start with the operation
Name the workflow, not the AI idea.
Send its monthly volume, the systems it crosses, who owns the result, what happens when it is late or wrong, and the best estimate of annual cost or leakage.
Request a 25-minute workflow triage If the workflow is not suitable for a paid diagnostic, Nathan will say so.