# Alternatives to Vellum

> Source: https://theagentsindex.com/vellum-ai/alternatives (re-verified)

Best match first.

## Shortlist

### 1. Agno

Python SDK plus self-hosted AgentOS runtime and hosted control plane for building and operating agents.

**Where it improves on Vellum:**
- [Debugs and fixes: yes — Bug fixing is a documented pattern: reproduce, patch, rerun the failing tests.](https://docs.agno.com/use-cases/coding-agents)
- [Reviews code: yes — Code review over a diff is one of the documented coding-agent patterns.](https://docs.agno.com/use-cases/coding-agents)
- [Whole-codebase work: partial — Repository-wide migrations are a named pattern, but the docs expect unresolved cases to be reported rather than fully landed.](https://docs.agno.com/use-cases/coding-agents)

**Trade-offs against Vellum:**
- [Open source: partial — The SDK and AgentOS runtime are open source and free at any scale, but the hosted control plane you pay for is not.](https://www.agno.com/pricing)

[View Agno](https://theagentsindex.com/agno)

### 2. Letta

Stateful agent harness, cloud and SDK for agents with persistent, git-versioned memory.

**Where it improves on Vellum:**
- [Debugs and fixes: yes — Vendor states coding agents debug failures and run test suites.](https://docs.letta.com/handbook/index.md)
- [Reviews code: yes — Reviews diffs on demand or on every PR via the GitHub action's prompt input.](https://docs.letta.com/platform/github-action/index.md)
- [Whole-codebase work: partial — Subagents read across large repositories and memory persists project knowledge, but no repo-wide migration claim.](https://docs.letta.com/configuration/subagents/index.md)

**Trade-offs against Vellum:**
- [MCP server: no — MCP runs inbound only: Letta sessions consume stdio, HTTP and SSE MCP servers; no Letta MCP server is published.](https://docs.letta.com/agent-sdk/mcp/index.md)
- [Opt out of training: partial — Hosted messages may train future models; running your own model backend or local state means nothing is collected.](https://www.letta.com/privacy-policy/)
- [Getting out: partial — Memory is git-backed files you can inspect and sync to your own GitHub repo; credit expiry is never stated.](https://docs.letta.com/handbook/index.md)

[View Letta](https://theagentsindex.com/letta)

### 3. Tale

Open-source project workspace where teams assign tasks to AI coding agents running in sandboxes.

**Where it improves on Vellum:**
- [Reviews code: partial — A separate agent can be granted a review tool to judge another agent's completed result and its evidence, but the vendor scopes this to task deliverables and says Tale does not verify GitHub state itself.](https://docs.tale.dev/platform/projects/task-automation)
- [Whole-codebase work: partial — Each project agent keeps a persistent sandbox workspace and may clone repositories, but the vendor documents no repository-wide indexing or migration capability and caps runs by time and sandbox capacity.](https://docs.tale.dev/platform/agents/harnesses)
- [Done-for-you service: partial — You run the software, but the Enterprise plan adds professional operation, installation and maintenance, with consulting and custom development charged hourly rather than a built-for-you agent.](https://tale.dev/pricing)

**Trade-offs against Vellum:**
- [Agent permissions: partial — Each agent is granted explicit tools, skills and secrets, connector writes are refused to the agent broker, and external automation writes pause for approval by default.](https://tale.dev/platform/governance)
- [On the command line: partial — A Tale CLI exists for deployment and configuration projects, and terminal agents can call the REST and MCP endpoints, but agent runs themselves are driven from the web app.](https://docs.tale.dev/develop/ai-assisted-development)

[View Tale](https://theagentsindex.com/tale)

### 4. Sim

Open-source AI workspace for building, deploying and running agents across 1,000+ integrations.

**Where it improves on Vellum:**
- [Reviews code: yes — Review Code mode checks out an existing PR read-only and submits a GitHub review with inline comments.](https://docs.sim.ai/workflows/blocks/pi)
- [Whole-codebase work: yes — Create PR clones the whole repository into a sandbox with full read, shell, edit and git access.](https://docs.sim.ai/workflows/blocks/pi)
- [Ships it: partial — Deploys what it builds: workflows ship as versioned REST endpoints, with deploy/undeploy/rollback callable from CI. What ships is workflows, not code.](https://docs.sim.ai/workflows/deployment/api)

**Trade-offs against Vellum:**
- [Writes code: partial — Generates workflow logic, blocks and schemas from a plain-English description, not application source code.](https://www.sim.ai/)
- [Opt out of training: partial — No customer-facing training opt-out switch; the vendor commits that Google-API data is never used for generalized model training, and self-hosting keeps data on your own infrastructure.](https://www.sim.ai/privacy)
- [Getting out: partial — Purchased credits never expire, but the weekly refresh allowance does not carry over; data leaves through the API, CLI and table exports rather than a one-click account export.](https://docs.sim.ai/platform/costs)

[View Sim](https://theagentsindex.com/sim)

### 5. n8n

Workflow automation platform for building and running AI agents on a visual canvas, with code where needed.

**Where it improves on Vellum:**
- [Ships it: partial — What it ships is the automation itself: publishing puts a workflow or agent version into production and schedules or channels then run it. It does not deploy application code.](https://docs.n8n.io/build/build-and-manage-agents)
- [Runs autonomously: yes — Agents run a reasoning loop until they produce a result and fire from schedules or channels with nobody watching; approval steps are something you add.](https://docs.n8n.io/build/build-and-manage-agents)
- [In your editor: partial — No n8n editor extension: the editor is a browser canvas. Cursor, VS Code and Windsurf reach the instance through its MCP server, so workflow building happens from the IDE via an agent.](https://docs.n8n.io/connect/connect-to-n8n-mcp-server)

**Trade-offs against Vellum:**
- [Writes code: partial — Authors n8n workflows from a plain-language description; the built-in assistant only gives guidance for the JavaScript or Python you write in a Code node, and it never touches application source.](https://docs.n8n.io/build/ways-of-building-workflows/ai-workflow-builder)
- [Writes tests: no — Native evaluations exist, but you supply the dataset and the expected outputs; no documented feature generates test cases for you.](https://docs.n8n.io/build/integrate-ai/test-and-improve-ai-workflows/understand-why-to-test)
- [Open source: partial — Source-available under the fair-code Sustainable Use License: free to use, modify and redistribute for internal business purposes, but not to resell or host for others. Files named .ee. sit under a separate enterprise licence.](https://docs.n8n.io/privacy-and-security/sustainable-use-license)

[View n8n](https://theagentsindex.com/n8n)

### 6. LangChain

Open source agent frameworks plus LangSmith, a hosted platform to trace, evaluate, deploy and govern agents.

**Where it improves on Vellum:**
- [Whole-codebase work: partial — Engine reads a whole connected repository to ground fixes and dcode carries context across sessions, but no page claims a repository-wide migration or multi-file refactor as a supported job.](https://docs.langchain.com/langsmith/engine)
- [Ships it: yes — LangSmith Deployment runs agents in production with one-click deploy from Studio and a control-plane API; the free Developer plan shows Deployment as N/A, so shipping starts at Plus.](https://docs.langchain.com/langsmith/studio)
- [Done-for-you service: partial — You run the software yourself on every self-serve plan; only Enterprise buyers get LangChain engineers, architectural guidance and team training alongside the product.](https://www.langchain.com/pricing)

**Trade-offs against Vellum:**
- [Self-hosted: partial — The open source frameworks run anywhere, but self-hosting or hybrid-hosting the LangSmith platform on Kubernetes is an Enterprise-plan option; Developer and Plus are cloud-only.](https://www.langchain.com/pricing)
- [Open source: partial — The frameworks and the dcode coding agent are MIT-licensed and free, while the LangSmith platform that carries the price, seats and governance is proprietary and hosted.](https://www.langchain.com/langchain)
- [Bring your own key: partial — You can bring your own provider keys through the gateway on every plan, or buy inference as Gateway Credits, but Engine refuses your keys and bills its model use as compute units.](https://docs.langchain.com/langsmith/engine)

[View LangChain](https://theagentsindex.com/langchain)