The decision owner, lawful access, representative non-sensitive cases, target environment, and people who can witness the result.
First pilots / qualification open
Apply intelligence to one problem that matters.
Bring one real problem, one environment, and one person who owns the decision.
NeuroForge is qualifying its first commercial, co-development, and research pilots. Success, failure, and stop conditions are agreed before work starts.
A good first pilot
One owner. One environment. One result worth knowing.
A good first pilot is small enough to control and important enough to change a decision—even when the answer is no.
Rights, data handling, funding, roles, baseline, acceptance criteria, security, publication, and stop conditions close in writing.
The owner sees the agreed cases, evidence, and failures—then chooses deploy, change, remediate, rescope, or stop.
Three different commitments
Choose the path that matches the question.
Each path has its own start gate, deliverable, risk boundary, and evidence. Interest alone does not change a candidate's status.
Fit-test-led commercial pilot
Start with the A$4,800 10-Day AI Fit Test. Ask whether one useful workflow fits the real machine, approved data, and operating limits.
- Qualification can begin now
- A stop or hardware-change decision is useful delivery
- No product or SLA implication
Product co-development pilot
Test one developed ERAIS surface in a partner environment—for example, whether a second operator can reproduce the workflow.
- Discovery and gate design are open
- Delivery waits for the candidate's entry gate
- No general-availability claim
Research pilot
Answer one falsifiable systems or model question under a frozen baseline, rights set, compute budget, and review path.
- Partner roles are explicit
- Null and negative outcomes remain valid
- Publication requires separate approval
Commercial pilot options
Four commercial engagements can enter qualification now.
The 10-Day AI Fit Test is the default first step. Every path ends with accept, remediate, extend, or stop—and a well-supported stop is useful.
10-Day AI Fit Test
What useful AI can run inside your actual data, hardware, connectivity, power, and accountability limits—and is deployment worth funding?
For A$4,800 ex GST, inspect the real system boundary, run a small local demonstration, and leave with the evidence to deploy, change the model or hardware, remediate—or stop.
Private AI Deployment Sprint
Can one valuable AI workflow run usefully inside your approved local hardware and data boundary?
Prove—or disprove—that one useful workflow can run locally, then leave with the tested system and the evidence behind the decision.
AI Evidence & Release Audit
Can one AI release be reconstructed and defended technically?
Reconstruct one AI release end to end—what it claims, what it used, what failed, what changed, and why the decision should be release, remediate, or hold.
Research & Benchmark Partnership
What does one controlled experiment say about a material technical or commercial decision?
Turn one important uncertainty into a pre-agreed experiment that a decision owner can act on and a reviewer can inspect.
If the Fit Test passes
Earn the next step. Keep an exit at every stage.
Larger commitments follow customer-visible evidence. They are not assumed at the start.
- 01Audit + local demo
Map the limits and show what works on the target machine.
- 02Staged local deployment
Deliver one workflow using the best-fit qualified model and runtime.
- 03Operate + update
Train the operator. Test every change. Keep restore and rollback available.
- 04Repeat + productise
Earn repeat sites, support, reusable software, or licensing from real use.
Gated co-development
Three candidates can enter discovery. None enters delivery by default.
ERAIS Gateway
Can one approved workload use a controlled local endpoint with the required operational controls?
Training Workbench
Can a second operator reproduce one bounded data-to-evidence workflow?
Evidence Control
Can a repeated release-evidence process become a reviewer-operable workflow?
Bring one useful problem
Tell us what must work, where it must work, and who decides.
The first conversation confirms what may be tested and what would justify deployment, a change of direction, or a deliberate stop.