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Gooey.AI vs Langflow

Two fact sheets from our own research, side by side — pricing, platforms, API access and status re-checked by us rather than quoted from the vendors. Gooey.AI publishes a starting price ($25); Langflow does not. Both have a free tier. Both ship a public API.

Gooey.AILow-code builder for forkable AI workflows deployed to WhatsApp, SMS, voice lines, Slack and web widgetsLangflowOpen-source visual builder for LLM agents and RAG flows, deployable as an HTTP API or an MCP server.

Side by side

FactGooey.AILangflow
CategoryAI Workflow BuildersLLM Orchestration Frameworks
Pricing modelFreemiumFree
Starts at$25 month—
Public APIYesYes
PlatformsWeb, APIWeb, macOS, Windows, Linux, API
CompanyDara.network IncLangflow
Last verifiedSep 6, 2026Sep 6, 2026

What our research says

Gooey.AI

One of the few workflow builders genuinely oriented to WhatsApp and voice deployments in low-connectivity regions, with forkable public recipes and model-agnostic plumbing. The catch is credit metering on every model call plus an enterprise band that jumps straight into five and six figures.

Pros

  • Deploys the same workflow to WhatsApp, SMS, voice, Slack and web
  • Public workflows are forkable, so you rarely build from zero
  • Model-agnostic across OpenAI, Google, Meta, Mistral and DeepSeek
  • Speech recognition and TTS aimed at underserved languages

Cons

  • Credits meter every step, making costs harder to predict
  • Enterprise pricing band is very wide and negotiation-driven
  • Niche positioning means a smaller community than mainstream rivals

Langflow

Langflow is the visual layer most teams reach for when a flow needs to be shown to someone who does not write Python, and the escape hatch into real code keeps it from becoming a toy. Deploying a flow as an API or MCP server in one step is the feature that earns it a place in production. The gap is commercial: no published pricing, no named vendor on the site, and support only via a contact form.

Pros

  • MIT-licensed with roughly 154,000 GitHub stars and an active release cadence
  • Any flow deploys as an HTTP API or an MCP server
  • Runs identically self-hosted, in the free cloud, or as a desktop app
  • Components can be edited as Python when the visual layer runs out

Cons

  • No pricing or support tiers published anywhere on the site
  • Desktop download requires a signup form and covers only Mac and Windows
  • The site names no operating company or jurisdiction
  • Visual flows get hard to reason about once they grow past a screen

Which one fits

Choose Gooey.AI if you need

  • NGOs and gov-tech teams shipping multilingual WhatsApp or IVR assistants
  • Product teams that want to fork a working AI workflow instead of starting blank
  • Orgs needing SOC2/HIPAA paperwork on a low-code stack

Choose Langflow if you need

  • teams prototyping RAG and agent flows visually before coding them
  • self-hosters who want an MIT-licensed orchestration layer
  • exposing a flow to other tools as an MCP server

More comparisons

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