Vercel Workflows makes your code durable. Avalanche runs the work your agents do.

Quick answer

Updated October 27, 2026. Vercel Workflows and Avalanche both pin running work to the deployed version it started on and let you roll back to an earlier version without a rebuild.[4, 6, 25] Choose Vercel Workflows if developers are writing durable backend code in TypeScript or Python for an app hosted on Vercel, which is generally available with managed infrastructure and preview deployments.[10, 12] Choose Avalanche if the job is a long, multi-step, document-heavy business workflow: you set the few steps, checks and approvals that matter, agents do the work inside each step, and every run keeps typed step outputs your team can compare across runs and versions.[21, 23, 25] Vercel traces the steps of your code; Avalanche records the business result of each step of agent work.[15, 25]

Key takeaway

Choose Avalanche when agents should do the work inside a few business steps you control, often over PDFs, Word files and spreadsheets.

Choose Vercel Workflows when developers want durable app code on Vercel with managed infrastructure and preview deployments today.

  • Avalanche wins on level of abstraction: you set the steps, checks and approvals; an agent does the work inside each step instead of code you write for every step.
  • Avalanche wins on document lineage: each step's file changes are committed as a new version of the run's workspace, and agent steps get PDF, Word and spreadsheet skills; with Vercel Workflows, a workspace is code you bring.
  • Tie on rollback: both return to an earlier version without rebuilding, and running work stays on its own version.
  • Vercel Workflows wins on availability today: Vercel Workflows is generally available with preview deployments; Avalanche Cloud is on a waitlist.

By , CTO, Trampoline AI. Updated · Facts checked · Published by the Avalanche team. Avalanche competes with Vercel Workflows.

01 / The core differenceAvalanche vs Vercel Workflows

Durable functions for your app, or agentic workflows for your business.

Vercel Workflows makes the functions a developer writes survive crashes, long waits and new deployments.[2, 4] Avalanche works a level higher: you describe the outcome and the few steps, checks and approvals that matter, and agents do the work in between, with each step checkpointed.[21, 25]

Vercel Workflows is infrastructure for developers: it makes the functions you write retry, sleep and resume, and pins each run to its deployment.[2, 4] Avalanche is built for the work agents do for a business: you define the few steps, checks and approvals that matter, agents do the work in between, and every run keeps its version and its typed step outputs.[21, 25] Both record every step; Vercel's traces help a developer debug code, while Avalanche's step outputs let a team compare the results of agent work across many runs. On deploys, versions and rollback, the two are close; the difference is the level you work at.[15]

02 / At a glanceChecked 2026-10-27

Avalanche and Vercel Workflows, side by side.

Avalanche and Vercel Workflows compared, checked 2026-10-27
CriterionAvalancheVercel WorkflowsEdge
Level of abstractionCoarse business steps: you set the steps, checks and approvals, and an agent does the work inside each step.[20, 25]A developer writes the orchestration and each step as code, marked "use workflow" and "use step".[2]Avalanche edge
From an agent skill to a workflowThe Avalanche skill for coding agents drafts a full workflow from a described outcome; agent steps also load Agent Skills (SKILL.md).[22, 27]Official skills help coding agents write or migrate Workflow SDK code; a skill loader inside steps is not documented.[13]Avalanche edge
Document lineageAvalanche Cloud: every run gets a versioned workspace; each step's file changes are committed as a new version, so you can see which step changed a file, compare versions and download any step's files; agent steps get PDF, Word and spreadsheet skills.[23, 25]Serializable values, binary data and streams cross steps; a persistent workspace and document parsing are code you bring.[2, 11, 23, 25]Avalanche edge
Inspecting and comparing runsAvalanche Cloud: typed inputs and outputs at every step checkpoint, in one run history filtered by status, flow and deployment; a web console with a live DAG of every flow and run, the inputs and outputs of any step in one click, and the full console in your terminal, so you can compare a step across many runs and versions.[21, 25]Every run records steps, inputs, outputs, sleeps and errors; the CLI and web UI inspect runs, steps, events and streams.[2, 15]Different jobs
Deploys and versionsAvalanche Cloud: each deploy is a frozen version of the whole workflow, mapped to an exact git commit, with locked, hash-verified dependencies; running workflows finish on the version they started on.[25]Each deployment is immutable; existing runs resume on their original deployment while new runs use the new one.[4, 14]Similar
RollbackAvalanche Cloud: instant rollback to any previous version from the CLI or console, no rebuild; running workflows are unaffected; an audit trail of who promoted or rolled back.[25]Roll back or promote an earlier production deployment without rebuilding; in-flight runs stay on their deployment.[6, 14]Similar
Recovery after a failureCompleted steps are recorded durably and never re-run after a crash; failed steps retry, and uncertain outcomes are held instead of blindly retried.[21, 25]Step results are recorded for replay; retries re-run failed work, not completed steps.[2, 9]Similar
Availability and environmentsSelf-hostable MIT-licensed runtime with operator, web console, REST API and terminal UI, more limited than Cloud; Avalanche Cloud is on a waitlist, with separate projects but no automatic previews.[20, 24, 28]Generally available on Vercel, with branch and pull request previews and custom environments.[10, 12]Vercel Workflows edge
Schedules, webhooks, CLI and APIAvalanche Cloud: cron schedules and webhooks declared in your workflow code, following rollbacks and promotions; webhook URLs never change on redeploy, redeliveries are deduplicated for 7 days, and idempotency keys return the same run for 7 days; a typed REST API with an OpenAPI spec, and a CLI.[25]Start runs from your API code, receive callbacks through hooks and webhooks, and schedule with durable sleep or chained runs; a CLI inspects runs.[14, 15, 16, 17]Similar
03 / Where each one winsOne claim per card

Where each one wins

Where Avalanche wins

  • Higher-level workflows

    You set the few business steps, checks and approvals that matter; an agent does real work inside each step. Python steps keep exact rules and arithmetic.[20, 25]

  • From a skill to a workflow

    Install the Avalanche skill with npx skills add Trampoline-AI/avalanche, describe the outcome in your coding agent, and it drafts the workflow with you.[22]

  • Every step versions your documents

    Avalanche Cloud gives every run a versioned workspace. Pass one document or hundreds; each step works on the files directly, and every step's changes are committed as a new version of the workspace, so you can see which step produced or changed each file, compare versions, and download any step's files. Document lineage, the way data teams have table lineage. Agent steps get PDF, Word and spreadsheet skills.[23, 25]

  • Versioned deploys and instant rollback

    On Avalanche Cloud each deploy is a frozen, checksum-verified version of the whole workflow, mapped to an exact git commit. Running workflows finish on the version they started on, and instant rollback makes any previous version live again in one click or one command, with no rebuild. Avalanche Cloud is on a waitlist.[25, 28]

  • Runs your business team can compare

    Each step is a business result with typed outputs, such as an RFP answer or a contract finding. Avalanche Cloud keeps every run by workflow and version, so you can compare one step across many runs.[21, 25]

  • Open source you own

    The runtime is MIT-licensed Python: versioned in git, reviewed in pull requests, run with the model provider you choose.[20]

  • Checkpointed Claude agent steps

    Agent steps can run Claude through the Claude Agent SDK and load Agent Skills (SKILL.md), each sandboxed and checkpointed like any other step.[26, 27]

Where Vercel Workflows wins

  • Durable code inside your app

    Mark functions with "use workflow" and "use step" in your existing app; the workflow ships with the rest of your backend.[2]

  • Generally available, managed

    Vercel Workflows is generally available, with functions, queues and persistence managed on Vercel.[1, 10]

  • Preview deployments

    Branch and pull request previews, staging branches and custom environments come with Vercel deployments.[12]

  • Step traces for developers

    Every run records its steps, inputs, outputs, sleeps and errors, and the CLI and web UI inspect runs, steps, events and streams.[2, 15]

  • Agents in code

    The AI SDK WorkflowAgent runs an agent loop inside a workflow, with typed tools, durable execution and tool approvals.[8]

04 / Detailed comparison4 buyer questions

What changes for your team.

01

Durable app code or business workflows?

Buyer question

Is the work part of your product's backend, or a business process your team repeats every week?

Vercel Workflows makes async functions durable. You mark a function with "use workflow" and the functions it calls with "use step"; step results are recorded, failed steps retry, and a run can sleep and resume across crashes and deployments.[2, 9] That fits app backends: onboarding sequences, order processing, or an agent inside your product.

Avalanche is built for long, multi-step business work that agents do, such as drafting RFP answers from past proposals or reviewing a stack of contracts. You set the few steps, checks and approvals that matter, agents do the work in between, and simple workflows fit the same model. On Avalanche Cloud, workflows run for hours or days, and an owner approves results before they go out.[25]

02

Versions and rollback: close on both sides

Buyer question

What happens to running work when you ship a change, or need to undo one?

On Vercel, each deployment is immutable and a run stays on the deployment it started on, through sleeps, retries and queued work. You can roll back or promote an earlier production deployment without rebuilding; runs already in flight keep going on their deployment, so Vercel's docs say to cancel them if they must stop.[4, 6, 14]

Avalanche Cloud works the same way at the workflow level. A deploy is a frozen, checksum-verified version; running workflows keep the code and bundled dependencies they started with, and you can roll back to any previous version in one click or one command, with no rebuild.[25] Avalanche Cloud is on a waitlist.[28]

03

Documents, agents and skills

Buyer question

How much do you want to build around the agent yourself?

In the Workflow SDK, values, binary data and streams cross step boundaries, and steps have full Node.js access, so document handling is code you write.[2, 11] Agents run through the AI SDK's WorkflowAgent, with typed tools, durable execution and tool approvals.[8]

In Avalanche, files move between steps, and on Avalanche Cloud each step's file changes are committed as a new version of the run's workspace. Agent steps declare typed inputs and outputs and get PDF, Word and spreadsheet skills.[21, 23] The Avalanche skill drafts the workflow from an outcome you describe in your coding agent.[22] Agent steps can also run Claude through the Claude Agent SDK and load Agent Skills (SKILL.md).[26, 27]

04

Running it in production

Buyer question

How mature does the managed service need to be today?

Vercel has the edge on availability. Vercel Workflows is generally available, with managed functions, queues and persistence, preview deployments per branch and pull request, and a dashboard that records each step, input, output and error.[1, 10, 12] Billing counts workflow events, data written and data retained, plus functions and queues usage.[3]

You can self-host the MIT-licensed Avalanche runtime, with its operator, web console, REST API and terminal UI, on your own infrastructure; it is more limited than Avalanche Cloud, which runs the production infrastructure for you.[20, 24] Avalanche Cloud adds SSO and organization roles, versioned deploys, instant rollback of the whole workflow with no rebuild, step checkpoints, managed queueing and one run history for every deployed workflow, and is open through a waitlist.[25, 28] Both record each step; the difference is what a step is. A Vercel step is a function a developer wrote, so its trace helps debug code. An Avalanche step is a business result an agent produced, with typed outputs, so a team can compare that step across hundreds of runs and see which outputs drift or which version changed them.[15, 21]

05 / FAQDirect answers

Common questions.

Is Avalanche an alternative to Vercel Workflows?
Partly. Both make multi-step work durable, version each deployment and roll back without a rebuild.[4, 6, 25] Vercel Workflows makes app backend code durable on Vercel; Avalanche runs business workflows where agents work inside a few steps you set, in MIT-licensed Python.[2, 20]
Does Vercel Workflows support rollback?
Yes. You can roll back or promote an earlier production deployment without rebuilding. Runs already in flight stay on the deployment they started on.[6, 14] Avalanche Cloud has instant rollback too: one click or one command makes any previous version of the whole workflow live again, with no rebuild, and running workflows finish on the version they started on.[25]
Can Vercel Workflows run AI agents?
Yes. The AI SDK's WorkflowAgent runs an agent loop inside a workflow, with typed tools that become durable steps and optional tool approvals. It replaces the deprecated DurableAgent.[8]
Is Avalanche open source?
Yes. The Avalanche runtime is MIT-licensed on GitHub.[20] The Workflow SDK behind Vercel Workflows is also open source, under Apache-2.0.[7]
How is Vercel Workflows billed?
By workflow events, GB of data written and GB-month retained, plus Vercel Functions compute and Queues usage, as of October 27, 2026.[3]
Can I see which step changed a document?
Yes, on Avalanche Cloud. Every run gets a versioned workspace, and each step's changes are committed as a new version, so you can see which step produced or changed each file, compare versions and download any step's files.[25] Vercel Workflows records each step's inputs and outputs and can pass binary data between steps, but its core docs do not define a persistent file workspace carried between steps.[2, 11]
How fast is Avalanche Cloud?
Measured October 27, 2026 on Avalanche Cloud v0.6.6, at the median (p50): a hello-world workflow ran end to end in 4.4 s, creating a run took 1.2 s, and each step started in 1.13 s. The web console loads cold in under 1 s. These are our own measurements of Avalanche Cloud, not a benchmark against Vercel Workflows.[25]
06 / SourcesChecked 2026-10-27

Public primary sources.

Every source was fetched on the date shown. Prices and plans change; check the vendor before you buy.

  1. [1]Vercel Workflows documentationVercel · Checked https://vercel.com/docs/workflow
  2. [2]Workflows and steps (Workflow SDK docs)Workflow SDK · Checked https://workflow-sdk.dev/docs/foundations/workflows-and-steps
  3. [3]Workflow pricing and limitsVercel · Checked https://vercel.com/docs/workflows/pricing
  4. [4]Versioning (Workflow SDK docs)Workflow SDK · Checked https://workflow-sdk.dev/docs/foundations/versioning
  5. [6]Promoting a deploymentVercel · Checked https://vercel.com/docs/deployments/promoting-a-deployment
  6. [7]vercel/workflow repository (Apache-2.0)Vercel on GitHub · Checked https://github.com/vercel/workflow
  7. [8]WorkflowAgent (AI SDK docs)Vercel AI SDK · Checked https://ai-sdk.dev/docs/agents/workflow-agent
  8. [9]Errors and retries (Workflow SDK docs)Workflow SDK · Checked https://workflow-sdk.dev/docs/foundations/errors-and-retries
  9. [10]A new programming model for durable execution (general availability)Vercel · Checked https://vercel.com/blog/a-new-programming-model-for-durable-execution
  10. [11]Serialization (Workflow SDK docs)Workflow SDK · Checked https://workflow-sdk.dev/docs/foundations/serialization
  11. [12]EnvironmentsVercel · Checked https://vercel.com/docs/deployments/environments
  12. [13]What's new (Workflow SDK docs)Workflow SDK · Checked https://workflow-sdk.dev/docs/whats-new
  13. [14]Workflows conceptsVercel · Checked https://vercel.com/docs/workflows/concepts
  14. [15]Observability (Workflow SDK docs)Workflow SDK · Checked https://workflow-sdk.dev/docs/observability
  15. [16]Scheduling (Workflow SDK cookbook)Workflow SDK · Checked https://workflow-sdk.dev/cookbook/common-patterns/scheduling.md
  16. [17]start() (Workflow SDK API reference)Workflow SDK · Checked https://workflow-sdk.dev/docs/api-reference/workflow-api/start.md
  17. [20]Avalanche repository and README (MIT License)Trampoline AI · Checked https://github.com/Trampoline-AI/avalanche
  18. [21]Results, cancellation, and reruns (Avalanche docs)Avalanche docs · Checked https://avalanche-docs.docsalot.dev/build-workflows/results-and-reruns
  19. [22]Build a workflow with the Avalanche skill (Avalanche docs)Avalanche docs · Checked https://avalanche-docs.docsalot.dev/build-workflows/build-with-skill
  20. [23]Skills for agent steps: PDF, DOCX and spreadsheet (Avalanche docs)Avalanche docs · Checked https://avalanche-docs.docsalot.dev/agent-steps/skills
  21. [24]Architecture and current limits (Avalanche docs)Avalanche docs · Checked https://avalanche-docs.docsalot.dev/reference/architecture-and-limits
  22. [25]Avalanche and Avalanche Cloud overviewAvalanche · Checked https://avalanche.run/
  23. [26]Pull request #124: Claude Agent SDK agent stepsTrampoline AI on GitHub · Checked https://github.com/Trampoline-AI/avalanche/pull/124
  24. [27]Pull request #136: Agent Skills (SKILL.md) in agent stepsTrampoline AI on GitHub · Checked https://github.com/Trampoline-AI/avalanche/pull/136
  25. [28]Avalanche Cloud waitlistAvalanche · Checked https://cloud.avalanche.run/waitlist
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See the runtime for yourselfOpen source · MIT

Our code speaks for itself.

The Avalanche runtime is open source under the MIT License. Read the code, run the starter project, and see how it fits the work your team repeats.