Giselle

Giselle assembles AI agents on a drag-and-drop canvas, so a workflow can be built and changed without hand-writing the orchestration. A single flow can call more than one model provider, which means no single vendor decides what the pipeline is able to do.

Running it locally takes a clone, a pnpm install and one provider key in an environment file, after which the development server serves the builder on port 3000. OpenAI, Anthropic and Google AI are supported, and at least one key is required. A hosted version offers the same features with free agent time each month, and a guide covers building with Giselle through AI coding assistants rather than a traditional editor.

The feature set is organized around delivery work rather than chat.

• GitHub operations: issues, pull requests and deployments handled by agents inside the existing workflow.
• Visual agent builder: agents created and modified through a drag-and-drop interface in minutes.
• Multi-model composition: GPT, Claude and Gemini in one flow, with agents choosing a model per task.
• Knowledge store: code and data searchable from one place, including GitHub vector store integration.
• Team collaboration: shared configurations and contextual awareness, still in development.
• Template hub: community-contributed agent templates for a one-click start, also in development.

Documented uses include a research assistant gathering from web and internal docs, a code reviewer wired into GitHub, a document generator producing specs and release notes, and a workflow automator chaining models across a business process. The project is under active development and licensed Apache 2.0.