Deploy AI locally with WorkingMouse to keep your data private, compliant, and secure. Our on-premise AI solutions give you total control,
data sovereignty, and the freedom to scale from small standalone systems to enterprise clusters without the risks or costs of public cloud
AI.
“For us, data sovereignty is a critical piece of the puzzle while trying to improve productivity and control costs. The Local AI solution provided by WorkingMouse is now called ‘HydroBrain’ and gives us exactly that.”
We offer Local AI deployment options that prioritise data sovereignty and deliver a clear return on investment by reducing reliance on external platforms. Organisations are under pressure to adopt AI, but face barriers with compliance and increasingly expensive cloud/SaaS fees. With proven expertise in infrastructure — from small standalone systems to self-hosted clusters — WorkingMouse makes Local AI simple to deploy, secure from day one, and built to scale.
WorkingMouse has replaced all paid GPT licences and development APIs with our own private LLM — built through research, mid-tier hardware investment, and self-hosted model configuration.
With on-premise AI, teams can:
One example is our ISO GPT, a knowledge base for our Management Systems that is accessible to the entire organisation. Local AI also enables private, secure collaboration on customer projects across teams.
Open-source LLM models give your organisation the freedom to run AI on your own terms — with no
black boxes and no hidden costs.
They deliver
transparency, flexibility, and full control, making them
ideal if you want to integrate AI into your business without sending data to the cloud or being locked into a third-party platform.
As part of our commitment to sustainability and a greener future, we’re planting one tree through ‘Carbon
Positive Australia’
in exchange for your contact details
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Learn AI basics in plain English. Our AI 101 webinar covers fundamentals, real-world use cases, and a safe adoption framework for businesses. Read More…
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Data Sovereignty or Cloud Convenience?
Explore data sovereignty, compliance with the Privacy Act, risks of foreign laws like the U.S. CLOUD Act, and practical guidance using a traffic light system to safeguard sensitive information Read More…
WorkingMouse installs Mac Mini AI hub at Hydrobiology, enabling private, in-house AI with Local AI for secure, scalable, and tailored environmental data analysis. Read More…
Mac Mini‑Powered AI: 5‑User Local Model Success
David Burkett interviewed the WorkingMouse AI R&D team to prove a 32 GB Unified‑Memory Mac Mini can run fast, privacy‑safe open‑weight AI for five users, with concurrency solved via an O Lama backend, while the team plans a company AI survey, will tap new Open AI/Google models on HuggingFace, and will soon scale experiments with an arriving Mac Studio. Read More…
Curious about AI at work? Our AI Reference Guide breaks down essential terms and concepts behind Large Language Models (LLMs)—including training, inference, RAG, and hardware requirements—to help teams adopt AI safely, locally, and productively. Ideal for business and IT leaders evaluating AI in enterprise settings. Read More…
AI You Own vs AI You Rent: What’s Better for Business?
Renting AI is risky and expensive. Shadow AI, rising SaaS costs, and data exposure are real threats. Hosting your own AI gives you control, lowers long-term costs, and keeps your data safe. Read More…
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Jidoka: Automation with a Human Touch, A Software Method to Gain Organisational Control
The Journal of Software and Systems Modeling published paper offers organisations a path to escape the legacy trap. Read More…
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Top 8 IT Consulting Trends for 2025
IT consulting in 2025 is driven by trends like AI integration, edge computing, and quantum advancements, helping businesses streamline operations, enhance security, and adopt sustainable practices. By staying ahead of these innovations, consultants empower organisations to remain competitive, adapt to challenges, and leverage emerging technologies for growth. Read More…
The Future of Digital Transformation in Government
By 2028, Queensland will advance digital transformation with digital IDs, cybersecurity, and inclusive services. Key goals include addressing diverse demographic needs, leveraging emerging technologies, and enhancing service delivery. Challenges involve managing legacy systems, data sovereignty, and attracting talent. Queensland's proactive approach aims to lead in digital innovation and set a high standard for government efficiency and engagement. Read More…
Embracing Abstraction for Cost-Effective System Development
Abstraction in system development involves focusing on core aspects by removing unnecessary details, which can revolutionise how organisations modernise and streamline their processes. Instead of discarding diagrams and artefacts, reusing them for higher-level models can boost productivity, consistency, and quality while cutting costs. The Jidoka philosophy, prioritising automation and quality over speed, highlights that investing in systematic abstraction leads to more cost-effective and agile development. Embracing this approach helps organisations balance quality with cost management and accelerates their path to innovation. Read More…
In February 2024, WorkingMouse shared insights on "Composite AI & Models for Modernising Government Services" with the Queensland Government Customer and Digital Group. Composite AI involves combining various AI tools to leverage their strengths and address their weaknesses. Key updates include using AI tools like CoPilot for coding, optimizing problems, platform engineering, team topologies, and modeling for shared understanding. The session highlighted the importance of human oversight alongside AI to ensure accuracy and quality. For more details, see the presentation slides and case studies linked. Read More…
Over-reliance on generative AI for creating code can lead to issues such as poor understanding, challenging debugging, and potential quality and security risks. AI tools like ChatGPT and GitHub Copilot are useful for generating code snippets and suggestions, but they lack the contextual awareness of human developers and can produce errors. It’s crucial to use AI as a collaborative tool rather than a complete solution, ensuring that human developers review, validate, and integrate AI-generated code to maintain accuracy, security, and adherence to best practices. Read More…
Made with ❤️ in Milton, Brisbane (Meanjin) Australia.
WorkingMouse acknowledges the Traditional Owners and their continuing connection to land, sea and community. We pay our respects to them, their Elders, both past and emerging.
2025 WorkingMouse Pty Ltd. All Rights Reserved.
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