JimuReport

JeecgBoot is an open-source enterprise AI low-code development platform. It combines online form, workflow, report, dashboard, portal, and application builders with an AI application platform for model management, chat, knowledge bases, workflow orchestration, MCP plugins, and other AI applications. Its AI Skills workflow accepts natural-language requirements and can generate database tables, SQL, front-end and back-end CRUD code, menu permissions, and rendered pages for a runnable business system. The platform also provides a conventional code generator for single-table, tree, one-to-one, and one-to-many data models, allowing generated code to be configured online and then manually merged and extended. Its knowledge-base features use large language models and RAG for document parsing, vector-store integration, retrieval, and question answering. The platform uses a separated Vue 3, TypeScript, Vite, and Ant Design Vue front end with a Java back end based on Spring Boot, Spring Cloud Alibaba, and MyBatis-Plus. It supports monolithic and microservice deployments, granular button, data, and field permissions, enterprise modules such as users, roles, organizations, messaging, and scheduled tasks, and integrations including Flowable, JimuReport, and JimuBI. JeecgBoot is distributed under the Apache License 2.0.

Helical Insight is an open-source business intelligence and embedded analytics platform for self-hosted, cloud, on-premises, and hybrid deployments. It combines natural-language, chat-driven AI analytics with bring-your-own-LLM support, automatic SQL generation, report summarization, and insight discovery; interactive dashboards with filters, KPI widgets, drill-down and drill-through interactions, maps, charts, pivot tables, and custom JavaScript visualizations; and paginated, pixel-perfect reports for invoices, financial statements, operational reports, and regulatory reporting. Dashboards, reports, and the AI chatbot can be embedded in web applications, SaaS platforms, customer portals, and enterprise applications. Reports and dashboards can be exported to PDF, Excel, CSV, Word, HTML, JSON, and XML, scheduled for delivery by email, and distributed as personalized reports. The platform supports white labeling, multi-tenancy, row-, column-, and table-level security based on user context, and SSO through JWT, Okta, Keycloak, OAuth, and custom token-based mechanisms. It connects to relational databases, NoSQL and big-data systems, flat files, cloud storage, and APIs through native connectors, JDBC, REST APIs, custom integrations, and uploaded JDBC drivers. Docker, Kubernetes, caching, pagination, virtualization, load balancing, clustering, and REST APIs support deployment and extension, while developers can customize it with Java, JavaScript, CSS, HTML, Liquid Template Language, plugins, and custom workflows. The project states that its enterprise features are available in the free open-source version.

Project Jupyter is an open-source web-based interactive computing platform centered on notebooks and computational kernels. JupyterLab provides a configurable interface for notebooks, code, and data, while the classic Jupyter Notebook offers a document-oriented web application for creating and sharing computational documents. Notebooks combine executable code with narrative text, equations, visualizations, and rich outputs, and use a JSON-based document format; kernels run code in a selected programming language and communicate with the notebook through a JSON-based interactive computing protocol over ZeroMQ and WebSockets. Jupyter supports more than 40 languages, including Python, R, Julia, and Scala, and includes JupyterHub for centrally deployed multi-user environments and Voilà for turning notebooks into stand-alone web applications.

BoardUI is a React design system for agentic interfaces and dashboards, combining AI-product components such as chat, thinking indicators, streaming agent logs, task lists, web-search trails, composers, and an agent runtime with dashboard components such as tables, charts, forms, cards, navigation, authentication, and design tokens. Its CLI copies individual components and their dependencies, or the complete free catalog, into a Next.js project as source files rather than installing a runtime dependency, so developers can modify the code directly. The system uses React Aria Components for accessible controls, Tailwind CSS v4, semantic design tokens, light and dark theme classes without runtime CSS, and Figma-based typography and styling rules. The repository includes a working AI chat application with a streaming chat endpoint and an agent runtime that accepts provider keys for supported services or an OpenAI-compatible server, reads keys server-side, and streams replies to the chat UI. It also provides an MCP server for browsing and installing components, along with agent rules specifying design tokens, type scale, and conventions.

QM is a multiplayer agent harness for startups that operates through Slack and a web interface. It gives each employee and room an isolated scope with its own memory, files, keychain view, permissions, scheduled jobs, web apps, and durable sandbox, while supporting collaboration in channels, group messages, and projects. Shared skills can be granted by scope, promoted by administrators, or imported from Git repositories; background work can run through crons, watches, and inbound webhooks, and internal apps can be published to selected users. A headless TypeScript core runs directly on Node with Fastify and handles identity, policy, scheduling, persistence, and the agent loop. Deployments can select harnesses and models including Pi, OpenCode, Codex, and Claude Code. PostgreSQL stores sessions, memory, queues, and other durable state, while a fixed tool surface includes an execute tool that runs commands in each scope's isolated, persistent sandbox. Slack is an optional in-process Bolt plugin; the web UI, admin panel, and public portal are optional HTTP API plugins built with Vite and Lit. Each deployment keeps organization-specific configuration, tools, skills, sandbox images, and infrastructure in a deployment directory validated and deployed by the qm CLI. Administrators can set organization-wide configuration, available harnesses and models, and a security posture. Strict mode pauses harness tool calls for human approval, Auto mode screens provenance-labelled external data and tool results with a classifier, and Dangerous mode disables content screening and pauses; a predeclared command policy with approvals and hard denials for operations such as recursive deletion or destructive SQL applies in every posture. Deployments run in the operator's own cloud account and are initialized from the @yc-software/qm package without requiring a source checkout; the project documents its threat model, operator assumptions, and known limitations in SECURITY.md.