After successfully crowd funding multiple R&D core activities, we decided to share our process to be compliant and successful.
A crowd‑funded R&D platform that guides teams through best practice, captures evidence, and keeps projects audit‑ready while the community funds each milestone.
Crowd-Funded Research & Development
Build the future together. Stay compliant, fund the research that moves Australia forward.
Service R&D guides teams through research & development compliance and best practice. Capture the full scientific process, publish evidence, and stay audit-ready while your community funds each milestone.
We teach the R&D lifecycle end‑to‑end: hypothesis, experimentation, evaluation, and documented outcomes.
Built for Australia: a structured process that aligns with R&D compliance expectations.
Focus areas: clean energy, climate tech, medical science, biotech, transport, defence, resources, agriculture, AI, quantum, and advanced computing.
Community outcomes: healthy ecosystems, thriving communities, and elevated Aboriginal and Torres Strait Islander knowledge systems.
Why crowd-fund R&D?
Open innovation builds trust. Share milestones, invite feedback, and let supporters fund the experiments that matter most.
Transparent milestones
Publish progress logs and evidence so backers can see outcomes as they happen.
Community-backed impact
Align funding with projects that strengthen technology, resilience, and social good.
Teams that deliver
Build multidisciplinary teams and keep knowledge moving from concept to deployment.
Compliance-First Workflow
Everything you need to meet exact R&D requirements
The workspace is built around the same documentation and evidence trail required for compliant R&D. Every step is captured so your project stays audit-ready from day one.
Built for Tax Agents & Firms
Export complete R&D datasets in minutes—structured evidence, financial records, and activity logs—so claims are prepared quickly and consistently.
Overview
Project metadata, scope, objectives, and timelines.
Planning
Planning documents and evidence that show intent and methodology.
Experimentation
Activity records, hypotheses, experiments, and outcomes.
Financials
Timesheets, invoices, contracts, and bank statements.
Logs & Exports
Trial logs, evidence capture, and CSV exports to prove compliance on demand.
Successfully Funded & Completed
Crowd-funded breakthroughs
These projects were completed with $280,000 in community funding and delivered with full R&D compliance documentation.
Black Box Computer
A breakthrough tiny local AI processing computer.
Crowd funded
$120,000
Autonomous Streaming Agent
An AI that can do everything a human can do in front of the camera.
Crowd funded
$90,000
AI Powered Marketplace
AI that brings products to customers faster than ever before.
Crowd funded
$70,000
Help crowd fund a project!
Public projects seeking support
Explore live research initiatives and back the breakthroughs that matter to you.
Black Box Continuation - Interactive Machine Intelligence Node
4traders pty ltd
Develop an Interactive Machine Intelligence Node (IMIN) that enables a user wearing AR computer-vision glasses, including devices such as Xreal One and similar wearable displays, to remotely control desktop software through a local AI computer. The system is intended to use microphone input, chat-to-model instructions, AR-oriented desktop/session context, multi-display computer-vision capture, native mouse/keyboard actions, and hand gesture control so the user can operate remote or local computer sessions without relying on vendor-provided APIs, workflow connectors, scripts, or traditional keyboard and mouse interaction. A central project objective is to determine whether IMIN can remember how different programs and sessions behaved previously. This session-context layer is technically important because arbitrary software control requires the AI computer to recognise visual state, recall previous layouts and failures, select appropriate OS-level actions, execute them remotely, and validate the result. Unlike software-specific automation, IMIN is being researched as a wearable AR control surface for arbitrary software. The local AI computer should observe screens, interpret visible interface elements, infer application state, plan actions, perform native input, recover from unexpected dialogs or changed layouts, and report results back to the AR glasses operator. The platform is intended for remote, industrial, emergency response, defence, field-service, and hazardous environments where hands-light operation, privacy, local processing, session continuity, and control of existing desktop tools are important. Objective: create an AR-glasses-based remote computer operator that lets a user speak, gesture, and visually supervise a local AI node controlling desktop software through computer vision and session memory.
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