Yonnie gives organisations a way to use AI on their own terms.
Instead of sending sensitive documents, records, and knowledge into public cloud AI systems, Yonnie is designed to operate locally through a secure compute node, a private AI layer, and simple workflow templates.
A dedicated local infrastructure layer that runs close to the organisation's data. Yonnie is designed around standardised local compute nodes. This helps simplify deployment, support, updates, and scaling while keeping the architecture repeatable across industries.
The private intelligence layer that processes documents, knowledge, and internal workflows. The Yonnie AI layer is designed to operate without exposing sensitive information to external model APIs. It can support document search, summarisation, drafting, review, and knowledge retrieval within a controlled environment.
A clean user interface tailored to each industry's work. The same secure backend can power different workflow experiences. The core infrastructure remains reusable. The front-end experience becomes specific.
Yonnie is not positioned as another open-ended chatbot. It is designed around structured workflows that match how regulated teams already work.
Search approved internal documents, policies, templates, and knowledge bases using natural language.
Create first-pass summaries of long documents, matter files, records, reports, or internal notes.
Generate working drafts, outlines, internal notes, letters, briefs, or summaries based on approved source material.
Help teams navigate complex files by extracting key dates, entities, issues, actions, and gaps.
Search and summarise internal policies, procedures, and regulatory guidance.
Give staff a controlled way to ask questions of approved internal materials without exposing sensitive content externally.
Enterprise AI does not need to feel heavy.
Yonnie is designed to feel more like a modern workspace tool than traditional enterprise infrastructure. The interface should be clear, modular, and easy to navigate, with workflows organised into simple boards, cards, search bars, document panels, and action buttons.
Users should know what each workflow does before they open it.
Templates should help users move from input to output without needing technical knowledge.
Each workflow can exist as a simple card, board, or workspace.
The product should feel approachable for non-technical teams.
Users should always understand what data is being used and what output has been generated.
The user chooses documents from an approved local source.
The user selects 'Matter Summary' from the legal workspace.
The AI reviews the selected material inside the controlled environment.
The output may include key parties, dates, facts, issues, missing information, and suggested next steps.
Yonnie supports professional work. It does not replace professional judgment.
Yonnie is designed as a repeatable deployment model.
A single local AI node can support multiple workflow templates. As the organisation identifies more use cases, additional templates can be added without rebuilding the core system from scratch.
Identify sensitive workflows where AI can create immediate value.
Define the required infrastructure, data boundaries, access rules, and approved use cases.
Launch a narrow, measurable workflow for a specific team.
Track time saved, user adoption, output quality, and operational value.
Add new workflow templates, departments, or additional nodes.
