Search Results for "textronics design software"
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Showing 7 open source projects for "textronics design software"
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Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Kodus
AI code reviews, just like your senior dev would do
Kodus-AI is a framework for building, training, and deploying intelligent agents and models, especially focusing on practical AI workflows for businesses and automation. It provides a structured set of tools and abstractions that help teams design agent behaviors, orchestrate data pipelines, optimize inference, and integrate AI capabilities with applications or services. The platform often includes model management, scalable training workflows, and orchestration patterns that help teams move... -
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Copperhead
Hardware as fast as software
Copperhead is an AI product-development agent for designing, documenting, and validating real printed circuit boards from natural-language requirements. It works directly with existing KiCad repositories instead of generating isolated mockups or diagrams. A full creation workflow can turn a product brief into specifications, architecture, component selection, schematics, an initial PCB layout, Gerber files, firmware scaffolding, and a development plan. The agent can also modify existing... -
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BMad Method
Breakthrough Method for Agile Ai Driven Development
BMad Method is a comprehensive AI-driven software development framework that structures the entire lifecycle of building applications through coordinated agent workflows and agile methodologies. It transforms AI from a reactive assistant into a structured team of specialized roles such as product manager, architect, developer, and QA, each operating within predefined workflows. -
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Expect
Let agents test your code in a real browser
...Overall, it serves as a lightweight but powerful tool for improving software reliability and clarity in testing workflows. -
Build Securely on Azure with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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Mermaid.js to SVG Converter
Visualize the diagrams of your projects
While coding with AI assist, I noticed bigger projects need something more rigid as context so the AI coder doesn't stray away when I try to add new features. You know, to keeps its memory fresh and not change the stuff that already works. The trick is to ask the AI to write a diagram in Mermaid.js format that solidifies the structure of the project and then use that as context to keep the AI reminded at all times what the project is as a whole. This will prevent it from changing things... -
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Aide
The open source AI-native IDE
Aide is an AI software engineering assistant that provides conversational code generation, analysis, and refactoring directly within your IDE or through a local web interface. Built to act as a full-stack collaborator, it understands multi-file projects, detects dependency relationships, and can generate consistent updates across files and frameworks. It supports multiple backends—including OpenAI, Anthropic, and open-source models—and can route requests based on task type or latency... -
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Kimi K2.7 Code
Coding-focused Kimi model for long-horizon agent workflows
Kimi K2.7 Code is a coding-focused agentic model built on Kimi K2.6, designed for long-horizon software engineering, autonomous coding workflows, and complex tool-based execution. It improves end-to-end task completion across real-world programming scenarios while reducing thinking-token usage by about 30% compared with K2.6. Architecturally, it uses a 1T-parameter Mixture-of-Experts design with 32B activated parameters, 61 layers, 384 experts, a 256K-token context window, and a MoonViT vision encoder. ...
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