Zerogate turns your company's data and expert decisions into a private AI model that you own. Built for Australian SMEs, hosted onshore.
Founding partners get priority onboarding and locked-in pricing.
The problem
Off-the-shelf models know the world, not your business. The advantage goes to companies that put their own data and judgement into the model.
Off-the-shelf AI
Zerogate
Method
Most businesses never need custom training. We only escalate when benchmarks on your own data show it's worth it.
Instructions, examples and tool access that make the model follow your process.
DaysLive lookups across your policies, manuals and past cases before every answer.
2–6 wksTraining on your best work for consistent format and conventions.
4–8 wksExperts choose the better draft, and the model learns the quality they recognise.
4–8 wksThe model practises your core task and is scored against confirmed outcomes.
2–4 mthsProcess
Four fixed-scope stages, each priced separately. You see measured results before committing to the next, and you keep everything delivered along the way.
Map the workflow, review data quality and privacy, and pick the highest-return task.
Output: ranked opportunity report
Build an expert-verified test set, then measure a leading model with retrieval on your real cases.
Output: working prototype and baseline score
Fine-tuning or reinforcement learning against a target score agreed up front.
Output: adapted model and before/after report
Integrate with your systems, with human review where it matters, monitoring and team enablement.
Output: production system and runbook
Offering
Compute and model fees are passed through at cost. Early-access partners lock in founding rates.
Data and ownership
For sensitive work we build on open-weight models hosted in Australia. The trained model is your asset, not a setting on someone else's platform.
Who it's for
If your team makes the same kind of decision hundreds of times a month, and you can tell right from wrong, we can train on it.
FAQ
We're onboarding a small group of early-access partners first. Join the list and we'll contact you as places open.
Priority onboarding, founding-partner pricing locked in, and direct input into how our tooling is built.
Retrieval works with the documents you already have. Fine-tuning and reinforcement learning usually need several hundred confirmed past examples. The Audit tells you exactly where you stand.
Only if you choose it. We can host open-weight models in Australian cloud regions or on your own infrastructure, and we confirm data residency in writing before any data moves.
Closed models are rented from their developer as a service. Open-weight models can be downloaded, hosted anywhere and trained freely. We use both, depending on your task, privacy needs and volume.
Before any build, we agree a target on a test set of real cases your experts have verified, such as accuracy, handling time or rework rate. Every report shows results against that target.
Join the list for priority onboarding and founding-partner pricing.