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J2Bot
J2Bot is a powerful Codebot on the Codebots platform that transforms structured models into fully functional full-stack applications instantly. By combining models, templates, and automated pipelines, J2Bot generates complete backend services (Java/Spring Boot), frontend components (React/TypeScript), PostgreSQL schemas, tests, and documentation from a single model. This eliminates weeks of manual coding, delivering production-ready applications in hours while ensuring consistency, quality, and traceability. J2Bot follows core principles like convention over configuration, separation of concerns, and continuous integration, making it a transformative tool for rapidly turning ideas into reliable software.
AI 101: The Basics Explained
Learn AI basics in plain English. Our AI 101 webinar covers fundamentals, real-world use cases, and a safe adoption framework for businesses.
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
Local AI in Action
WorkingMouse installs Mac Mini AI hub at Hydrobiology, enabling private, in-house AI with Local AI for secure, scalable, and tailored environmental data analysis.
Modernising with Jidoka
Jidoka, the principle of “automation with a human touch” popularised by Toyota, is being reimagined for software and AI. Dr Eban Escott
showed how humans and machines working together can make automation more reliable, adaptable, and effective.
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.
AI Reference Guide
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.
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.
Need product-ready technologists without the long-term risk?
Scale your dev team in 5 days with Talent-as-a-Service: pre-vetted, security-cleared developers & designers, no HR hassle.
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.
Why Discovery Matters
Modernising legacy systems starts with Discovery—understanding what exists, capturing real business needs (not just assumptions), and identifying risks early. At WorkingMouse, this means engaging SMEs, modelling requirements with traceability, and focusing on like-for-like modernisation to reduce risk before optimisation. Discovery sets the foundation for successful delivery by aligning goals, compliance, and technical feasibility right from the start.
Why Estimations Are So Hard
WorkingMouse tackles estimation with a structured, evolving process grounded in real-world data, team experience, and open communication. Discover how we turn uncertainty into clarity.
Learn about our process and solutions:
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