Local AI Node
Runs on dedicated local compute infrastructure controlled by the organisation.
Private AI infrastructure for regulated teams
AI your organisation can use without giving up control of its data.
Yonnie is a local AI platform designed for organisations that cannot rely on public cloud AI tools because of privacy, compliance, or data sovereignty requirements.
It brings useful AI workflows into secure environments by running on local compute infrastructure, with no dependency on external model APIs.
Built for sensitive industries. Designed for local deployment. Preparing anchor pilots in Melbourne.
The problem
Most organisations want AI. Their data policies say no.
Large language models are changing how work gets done. But many organisations cannot safely use public AI platforms because their data is sensitive, regulated, confidential, or commercially valuable.
For these teams, the question is not whether AI is useful.
The question is: Where does the data go?
Legal firms, clinics, schools, councils, and professional service providers manage information that cannot be casually uploaded into cloud systems. Even when the potential productivity gain is obvious, the procurement risk is often too high.
Yonnie is designed for that gap.
The product
Yonnie brings AI into the building.
Yonnie is a private AI node that can be deployed locally inside an organisation's own environment.
It combines local compute, a secure AI layer, and simple workflow interfaces so teams can search, summarise, draft, review, and organise internal knowledge without sending sensitive information to public cloud AI providers.
Private AI Brain
Processes internal documents and knowledge without relying on external AI APIs.
Workflow Templates
Turns the same secure AI backend into practical tools for legal, medical, education, municipal, and professional workflows.
Simple User Experience
Designed to feel familiar, clean, and easy to use - more like a modern productivity app than complex enterprise software.
How it works
One secure engine. Many specialised workflows.
Yonnie separates the secure AI infrastructure from the user interface. That means the core system can remain standardised while each client gets a workflow experience that feels specific to their industry.
Deploy locally
Yonnie is installed on local compute infrastructure, reducing dependence on public cloud processing.
Connect approved knowledge
The organisation selects which documents, policies, records, templates, or internal knowledge sources can be used.
Choose workflow templates
Teams access specific tools such as matter summaries, policy search, case preparation, patient history summaries, planning document review, or internal knowledge assistants.
Keep sensitive data inside the environment
The AI workflow runs locally, supporting productive work without exposing confidential material to external systems.
Use cases
Built for the teams cloud AI cannot easily reach.
Yonnie is designed for sectors where data privacy is not optional.
Private AI for law firms
Summarise matter files, prepare chronologies, search internal precedents, review large document sets, and draft first-pass working notes inside a controlled environment.
Explore legalPrivate AI for clinics and health teams
Support administrative summaries, patient history review, referral preparation, and internal documentation workflows while keeping sensitive health information local.
Explore medicalPrivate AI for schools and education providers
Help staff search policy documents, summarise internal guidance, prepare administrative material, and support knowledge management without exposing student or staff data to public AI systems.
Explore educationPrivate AI for councils and municipal teams
Assist with policy search, planning document review, resident service history summaries, internal knowledge access, and operational documentation.
Explore local governmentPrivate AI for accounting, consulting, and advisory firms
Summarise client files, search internal knowledge, draft working papers, support compliance review, and accelerate research without sending confidential client material outside the organisation.
Explore professional services Why Yonnie
Useful AI should not require a privacy compromise.
Most AI products are designed cloud-first. Yonnie is designed privacy-first.
Instead of asking regulated organisations to change their risk posture, Yonnie starts with the constraint that matters most: sensitive data must stay controlled.
Cloud AI
- Fast to access
- Broadly useful
- Often dependent on external APIs
- Difficult for sensitive data workflows
- Can trigger procurement and compliance concerns
Yonnie
- Designed for local deployment
- Built for sensitive workflows
- Uses a standardised private AI architecture
- Adaptable through workflow templates
- Created for enterprise procurement realities
Seed-stage momentum
A focused wedge into a large regulated market.
Yonnie is being built around a clear market entry strategy: start with the organisations most blocked by cloud AI, prove the product in demanding privacy environments, and expand through repeatable workflow templates.
Our first target market is Melbourne-based professional and legal organisations where privacy requirements are high, workflows are document-heavy, and AI value is immediately visible.
Investor thesis
See the market thesis behind Yonnie.
Yonnie is preparing its first anchor pilots and investor materials.
Pilot program
Now preparing anchor pilot deployments.
Yonnie is looking for early anchor partners in regulated sectors who want practical AI capability without moving sensitive information into public cloud systems.
The pilot program is designed to validate real workflows, measure time savings, refine templates, and produce a strong privacy-first AI case study.
- Local AI workflow discovery
- Secure deployment planning
- Initial workflow template selection
- Staff feedback sessions
- Productivity and adoption measurement
- Case study development, subject to approval
Final call to action
Bring AI closer to the work - without sending the work away.
Yonnie is for organisations that need AI capability, but cannot compromise on privacy, compliance, or data control.