Budibase
An open-source operations platform that builds AI agents, automations, and apps to handle requests, approvals, and system integrations — saving engineers hundreds of hours.
- Source repo
- Budibase/budibase
- Stars
- ★ 28k
- Last updated
- 2d ago
- License
- NOASSERTION
- Primary language
- TypeScript
- FA score
- 52/100 · Major gaps
At a glance
- How it runs
- Works with
- Universal · cross-platform
- Cost
- Free tier plus a paid hosted plan
- Setup effort
- Medium · a few setup steps
- You'll need
- Typical use
- IT teams self-host the platform to centrally handle employee ticket requests, approval requests, and issue reports
- Not a fit if
- Teams wanting to avoid vendor cloud and paid-license restrictions
- Teams unwilling to learn its app-building and automation system
- Teams needing fully offline operation without external AI models
- Source review
- 52/100 · Major gaps
What does this agent do, and when should you use it?
Budibase is an open-source operations platform for building AI agents, automations, and apps that actually run business operations. Its agents go beyond answering questions — they execute workflows across a business, such as creating records, routing approvals, updating apps, and notifying teams. The platform integrates with databases, AI models, and business apps, and is model agnostic. The codebase is a lerna-managed monorepo with three core packages: builder (a Svelte front-end), client (a browser-side rendering module), and server (a Koa backend). Deployment options include self-hosting via Docker, Docker Compose, Kubernetes, Digital Ocean, or Portainer, plus a hosted Budibase Cloud. Licensing is GPL v3 for the platform, MPL for the client/component libraries, and Business Source License for paid features.
Employees ask questions, request approvals, or report issues through a chat interface; Budibase agents understand the requests and act automatically — running workflows across business systems, creating records, routing approvals, updating apps, and notifying teams. The platform connects to databases, AI models, and business apps as data and action sources; enables low-code construction of CRUD apps and internal tools; and exposes the Budibase Public API so Budibase can serve as a backend and interoperate with other systems. Administrators can globally manage users, onboarding, SMTP, apps, groups, and theming, and can delegate user management to group managers via portals.
- IT teams self-host the platform to centrally handle employee ticket requests, approval requests, and issue reports
- Engineering teams rapidly build internal CRUD tools connected to SQL databases without stitching multiple systems together
- Operations teams configure agents to automatically route approvals and notify the right teams instead of manual dispatch
- Enterprises use the Public API to run Budibase as a backend serving data and apps to existing systems
- Admins need centralized management of users, SMTP, apps, and theming across multiple apps and groups with delegated permissions
How do you install or deploy this agent?
Self-host: follow https://docs.budibase.com/docs/hosting-methods, with options for Docker (a single ARM-compatible image), Docker Compose, Kubernetes, Digital Ocean, and Portainer. Or skip self-hosting and register for Budibase Cloud at https://account.budibase.app/register.
How do you use this agent?
After deployment, use the builder (Svelte client) to visually build apps, automations, and agents; connect databases, AI models, and business apps as data sources and action targets; employees then submit requests via the agent chat UI and agents execute workflows automatically. Developers can integrate via the Budibase Public API: get an API key and consult the general docs (https://docs.budibase.com/docs/public-api) and interactive API docs (https://docs.budibase.com/reference/appcreate).
What are this agent's strengths and limitations?
- Agents perform real actions — creating records, routing approvals, updating apps, notifying teams — not just answering questions
- Model-agnostic design with integrations for multiple AI models
- Fully self-hostable via Docker/Kubernetes, keeping data on your own infrastructure with centralized user and permission management
- Includes a Public API so Budibase can act as a backend and interoperate with other systems
- Client and component libraries are MPL licensed, so apps you build can be licensed however you like
- The core platform is GPL v3 and paid features fall under the Business Source License — commercial use requires evaluating modification and redistribution restrictions
- No published pricing, performance benchmarks, or evidence of agent execution reliability; effectiveness must be verified on your own
- Its platform paradigm (builder + database + workflows) creates migration costs if you later switch to another solution
- Full value requires learning its app-building, automation, and agent configuration system — a real learning curve
- The repository does not detail the API key issuance process or list which specific AI models agents support
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 |
|---|---|---|---|---|---|---|
| Budibase This agent | 52 · Major gaps | Self-hosted serviceFreemium | ★ 28k | 2d ago | TypeScript | — |
| OpenOps | 59 · Major gaps | Self-hosted serviceFreemium | ★ 1.1k | 2d ago | TypeScript | — |
| Flow-Like | 55 · Major gaps | Desktop appFreemium | ★ 967 | 3d ago | Rust | — |
| ByteChef | 53 · Major gaps | Self-hosted serviceFree + model costs | ★ 1k | today | Java | OpenAI API · Claude API |
How does FollowAgents rate this agent?
Why each dimension lost points
Positives: least-privilege GitHub permissions in CI workflows, dependency resolutions pinning known-vulnerable transitive packages, a security:audit script, SECURITY.md disclosure process, and explicit rollback documentation in the CI README. Deducted: LLM keys (BBAI_LITELLM_KEY/LITELLM_MASTER_KEY) passed via env vars with no sensitive-data handling policy shown; README asserts agents automatically create records, route approvals and act across systems with no demonstrated user-confirmation, scoping, or external-effect controls; securityContext is not rendered by default in Helm; pinning covers only a subset of dependencies.
Consistent package structure, pinned Node engines, resolutions, and lerna build chain; README and package. corroborate each other. Deducted: failure behavior evidenced only by basic Helm test-connection probes; runtime failure handling for agents/automations has no in-repo evidence, and core agent docs point off-repo so cannot be verified here.
Environment fit earns full marks: single ARM-compatible Docker image, Compose, Kubernetes, DigitalOcean, Portainer, air-gapped and multi-arch builds are all documented/scripted. Deducted: audience description is present but thin; capability boundaries of the agents are undefined; trigger precision is marketing phrasing ('understand these requests') with no mechanism; model-agnosticism asserted without evidence.
Information architecture is thorough — monorepo package responsibilities, CI pipeline directory docs, contributing guide, code of conduct — justifying full marks. Licensing guidance is detailed (GPLv3/MPL/BSL with selection rules) but repo-level metadata is NOASSERTION and the multi-license split adds compliance burden, so 2. Install instructions defer to an external docs site; no examples/FAQ/CHANGELOG in evidence; known limitations limited to the 'latest major only' patch policy; maintenance responsibility has a documented vulnerability release process but versioning/changelog evidence is weak.
Output usability is moderate: apps/automations/public API delivery forms are clear but unverified without execution. Marginal value deducted: the differentiating 'AI agents run your operations' claim rests on screenshots and assertions, not in-repo proof of advantage over existing low-code+automation platforms. Cost-benefit: self-host vs cloud paths and air-gap support reduce cost, earning a 2.
Cross-source corroboration is decent: README, package., Helm chart/tests, and CI docs are mutually consistent. Deducted: marketing figures ('saves 100s of hours', 'securely') are untraceable; facts and promotional inference are heavily mixed without separation; no in-repo verifiable spec or evaluation of agent behavior (a RAG evals script entry exists but no results).
- Agents 'take action across your business' with no in-repo evidence of user confirmation or permission scoping; audit external-effect paths before deploying.
- LLM keys are injected via environment variables (BBAI_LITELLM_KEY); verify key rotation, log redaction, and transport encryption.
- Helm deployments render no securityContext by default; explicitly set runAsNonRoot/readOnlyRootFilesystem in production.
- Repo-level license metadata is NOASSERTION; actual licensing is a GPLv3/MPL/BSL mix — check per-package licenses before commercial use, especially BSL production-use restrictions in packages/pro.
- Security patches apply only to the latest major version; upgrade promptly.
- This was a static review; no builds or agent behavior were executed or tested.
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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v3.51.0-cloud.7 Pre-release
Release notes excerpt
What's Changed * Allow JavaScript S3 upload filename bindings by @melohagan in https://github.com/Budibase/budibase/pull/19895 Full Changelog: https://github.com/Budibase/budibase/compare/v3.51.0-cloud.6...v3.51.0-cloud.7View on GitHub ↗