Giselle
A visual AI workflow builder for product-delivery and GitHub automation work.
- Source repo
- giselles-ai/giselle
- Stars
- ★ 559
- Last updated
- 3d ago
- License
- Apache-2.0
- Primary language
- TypeScript
- FA score
- 43/100 · Major gaps
At a glance
- How it runs
- Works with
- Universal · cross-platformOpenAI API · Claude API
- Cost
- Free tier plus a paid hosted plan
- Setup effort
- Low · running in minutes
- You'll need
- Typical use
- An engineering team that wants AI automation around GitHub issues, pull requests, or deployments.
- Not a fit if
- Teams that need fully offline or local-model operation
- Teams waiting for Team Collaboration and Template Hub to ship
- Teams needing documented GitHub permissions and token setup
- Source review
- 43/100 · Major gaps 3 safety controls not found
What does this agent do, and when should you use it?
Giselle is an open-source AI app builder for agentic workflows and human-AI collaboration. Its Visual Agent Builder provides a drag-and-drop interface for creating and modifying agents, while multi-model composition covers GPT, Claude, Gemini, and more. The Knowledge Store is described as a place to access and search code and data, with GitHub vector store integration supported. Giselle targets GitHub operations, code review, research, document generation, and chained business workflows; it is available as a self-hosted application and a hosted cloud service.
Users create and modify agents through the drag-and-drop Visual Agent Builder, then compose workflows that can use GPT, Claude, Gemini, and other models. The Knowledge Store accesses and searches code and data, and the README explicitly notes GitHub vector store integration. For GitHub operations, Giselle is described as automating issues, PRs, and deployments with AI. Listed outputs include code-review work, PRDs, specifications, and release notes. For local use, install dependencies with pnpm install, place at least one provider API key in .env.local, run pnpm turbo dev, and open http://localhost:3000.
- An engineering team that wants AI automation around GitHub issues, pull requests, or deployments.
- A product or development user who needs to assemble a multi-model workflow visually instead of starting with hand-written orchestration.
- A team that needs AI to search its code and data, including a supported GitHub vector store integration.
- A product-delivery team generating PRDs, specifications, or release notes from its codebase.
- An internal automation user chaining several models for a more complex business process.
How do you install or deploy this agent?
Run: git clone https://github.com/giselles-ai/giselle.git && cd giselle && pnpm install. Create .env.local and add at least one provider key, for example OPENAI_API_KEY="your_openai_api_key_here". The README also lists Anthropic and Google AI as supported providers. Start the application with pnpm turbo dev.
How do you use this agent?
After pnpm turbo dev starts, open http://localhost:3000 and begin building AI agents with the drag-and-drop Visual Agent Builder. Configure at least one OpenAI, Anthropic, or Google AI API key in .env.local before starting the application. The documented workflow can compose GPT, Claude, Gemini, and other models, while the Knowledge Store is described for accessing and searching code and data. The supplied README does not document detailed workflow publishing, GitHub authorization, or production deployment commands.
What are this agent's strengths and limitations?
- It explicitly supports composing GPT, Claude, and Gemini in the same workflow.
- The drag-and-drop Visual Agent Builder gives users a visual way to create and modify agents.
- Its Knowledge Store is intended for code and data search, with GitHub vector store integration called out directly.
- The repository identifies concrete engineering uses: GitHub issue, PR, and deployment automation; code review; and delivery-document generation.
- Self-hosting requires at least one API key from OpenAI, Anthropic, or Google AI, creating an external provider dependency.
- The public roadmap is still being created, and Team Collaboration and Template Hub are marked In Development.
- The README does not specify the permissions, token setup, or authorization flow for GitHub operations.
- No concrete documentation is supplied for production deployment, model-routing behavior, workflow observability, or failure handling.
How does this agent compare with similar options?
Key facts side by side with the most closely related agents.
| Agent | Source review | Form / cost | Stars | Updated | Language | Full support on |
|---|---|---|---|---|---|---|
| Giselle This agent | 43 · Major gaps | Self-hosted serviceFreemium | ★ 559 | 3d ago | TypeScript | OpenAI API · Claude API |
| Webwright Browser Coding Agent | 66 · Some gaps | CLIFree + model costs | ★ 6.1k | 10d ago | Python | Codex · Claude Code · OpenAI API · Claude API |
| ReadmeAI - AI-Powered README Generator | 51 · Major gaps | CLIFree + model costs | ★ 3k | 2mo ago | Python | OpenAI API · Claude API |
| Stripe AI | 50 · Major gaps | Library / SDKFree + model costs | ★ 2k | 1d ago | TypeScript | Codex · Claude Code · OpenAI API · Claude API |
How does FollowAgents rate this agent?
Why each dimension lost points
Evidence shows: CI workflow uses least privilege (contents: read), dependency overrides show attention to dependency security, SECURITY.md provides reporting channels. Deductions: no user confirmation mechanism, data flow transparency, sensitive data handling details, rollback mechanism; external effects (e.g., GitHub operations) not detailed; publisher identity unverified, source attribution only based on repository metadata.
Evidence shows: consistent project structure, uses turbo and pnpm, CI includes tests and type checks, dependency overrides ensure availability. Deductions: failure messages not explicit in docs, error handling details insufficient.
Evidence shows: README clearly identifies target users (developers and non-engineers), provides multiple use cases and self-hosting guide, environment requirements (Node >=24) explicit. Deductions: capability boundaries not clear, trigger precision (e.g., specific triggers for GitHub operations) not specified.
Evidence shows: README structure clear, installation steps detailed, license Apache-2.0, contribution guide and security policy present. Deductions: version only 0.1.0, no changelog file, known limitations not explicitly listed.
Evidence shows: output usability high (cloud service and self-hosting), marginal value evident (automating workflows), cost-benefit not detailed (free tier and open source). Deductions: cost-benefit analysis insufficient.
Evidence shows: feature claims in README have some support (e.g., GitHub integration), but lack detailed documentation or test evidence. Deductions: claim-evidence correspondence incomplete, cross-source verification limited, facts and inferences not clearly separated.
- Not found in source: confirmation before actingTurn on (or add) a confirmation step before it acts, and try it in a sandbox or test environment before real data.
- Not found in source: data-flow disclosureWatch which external services it contacts (proxy or firewall logs) and keep sensitive data out until you know where it goes.
- Not found in source: rollback or recovery pathBack up first, or work on a git branch or snapshot, so its changes can be undone.
- Publisher identity unverified; treat source with caution.
- No user confirmation mechanism found; may execute external actions automatically.
- Sensitive data handling details not disclosed; review yourself.
- Version 0.1.0 indicates early development; API may be unstable.
Recent releases
Latest entries from the project's GitHub Releases. Notes are quoted from upstream as written, not rewritten or tested by FollowAgents.
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Release notes excerpt
What's Changed Maintenance - chore: remove Google URL Context feature (#2880) @shige - chore: drop stale WAITUNTIL_OFFSET_MILLIS passthrough (#2882) @shige Full Changelog: https://github.com/giselles-ai/giselle/compare/v0.75.5...v0.75.6 Originally released: 2026-04-21View on GitHub ↗ -
Release notes excerpt
What's Changed Dependencies - fix(deps): bump protobufjs from 7.4.0 to 7.5.5 (#2877) @shige Full Changelog: https://github.com/giselles-ai/giselle/compare/v0.75.4...v0.75.5 Originally released: 2026-04-17View on GitHub ↗ -
Release notes excerpt
What's Changed Maintenance - chore: clean up unused pnpm catalog entries and remove knip catalog exclusion (#2851) @legasik21 Bug Fixes - fix(ci): add explicit permissions to GitHub Actions workflows (#2875) @shige Dependencies - fix(deps): bump happy-dom from 20.0.2 to 20.8.8 (#2862) @shige - fix(deps): bump next from 16.1.7 to 16.2.3 (#2864) @shige - fix(deps): bump @trigger.dev/sdk and CLI from 4.3.0 to 4.4.4 (#2865) @shige - fix(deps): bump vite from 7.3.1 to 7.3.2 (#2866) @shige - fix(deps): bump systeminformation from 5.23.8 to 5.31.5 (#2867) @shige …View on GitHub ↗