Dystr

• Cloud-based secure workspaces for projects with code, data, notes and files
• Chat assistants that respond to natural-language prompts and work interactively
• Worker assistants that run scheduled or triggered tasks for automation
• Compute environment integrated with data, code and AI models
• File system for storing datasets, documentation, version control and results
• Support for engineering calculations, visualisations and analysis workflows
• Integration of AI assistants with files, compute and workspace context
• Collaboration tools for engineering, electrical and mechanical teams
• Low-code/no-code interface enabling non-software engineers to automate tasks
• Strong isolation of workspaces to maintain project boundaries and data security

Dystr is a specialised platform designed for engineering, technical and research teams seeking to automate workflows, manage code, data and documentation, and deploy AI assistants in a unified environment. With Dystr, users create isolated cloud workspaces where files, compute environments, notes and AI models coexist. Each workspace functions as a secure project lab where code runs, data is processed, documentation evolves and AI assistants act. The Chat assistants respond to user prompts and maintain conversation context, enabling exploratory workflows, while Worker assistants can be scheduled or triggered to perform recurring or event-driven tasks such as monitoring data sources, generating reports or updating documentation. The platform provides a low-code/no-code interface which helps mechanical, electrical or systems engineers who may not be full-time software developers to leverage automation and AI. It also supports collaboration among team members with versioned files, shared compute resources, notes and results. With visualisation tools built in, engineering calculations and datasets become more accessible and transparent. Dystr is particularly relevant for teams working in heavy engineering domains such as manufacturing, research, design, simulation or data analysis, where repetitive or computationally intensive tasks can be offloaded to AI agents. Because the workspaces are isolated, data and models are contained securely, enabling safe collaboration and iteration. For organisations looking to improve productivity, reduce manual workload, and bring AI-assisted workflows into engineering projects, Dystr offers a modern, cloud-native environment tailored for these needs.