Anfloy vs Gumloop.
Gumloop is the cleanest visual builder we've seen for AI workflows - drag, connect, run. It works beautifully right up until the workflow needs branching logic, custom retrieval, or behavior that doesn't fit a node. Past that point you're back to writing code. We start with code. So when complexity arrives, the system absorbs it.
Why not just use Gumloop?
Visual AI workflow automation. The table reads Gumloop on the left, Anfloy on the right - both honest.
Visual canvas. Connect nodes.
Code in your repo.
Limited to their conditional nodes.
Any control flow your language supports.
Hard. You're stuck with their RAG.
Any vector store, hybrid search, or custom heuristic.
Their integration catalog.
Anything with an API.
Their UI history.
Git. Real test suite. Real CI.
Subscription + per-run credits.
Flat build cost. Bring your own LLM keys.
When Gumloop is the right call
- The workflow is straightforward and fits a linear chain of LLM + tool calls.
- You want the team to see and edit the workflow visually.
- You're prototyping and don't want to commit to engineering effort yet.
- You're fine with the workflow living in their cloud forever.
When Anfloy is the right call
- The agent needs branching logic, retries, custom retrieval, or state across runs.
- You want the workflow versioned in Git and tested in CI.
- Your stack includes internal tools no visual builder integrates with.
- You expect to extend the system over the next 12 months and don't want a node-library ceiling.
Anfloy vs Gumloop, answered.
Are visual builders like Gumloop just easier to maintain?
For simple workflows, yes - anyone can read the canvas. But once branching, retries, or state appear, a visual representation of complex code is harder to reason about than the code itself. The break-even is somewhere around 8–10 nodes.
Can we use Gumloop and Anfloy together?
Yes - and it's a common combo. Keep simple workflows in Gumloop for the non-engineering team to own; have us build the load-bearing agents in code, with Gumloop calling them as a step when useful.
What happens when Gumloop's runtime changes?
You inherit whatever changes they ship. With Anfloy code in your repo, you decide when to upgrade dependencies. Less platform risk.
Why not just hire someone to build agents in code?
You can - and we encourage it long-term. We're faster because we've shipped this pattern 30+ times. First build is faster with us; your in-house team takes over later.
Three more head-to-heads.
No-code workflow automation.
Sales data enrichment platform.
Hiring a full-time AI engineer.
Traditional agency or AI consultancy.
No-code AI agent platform.
AI SDR / outbound platform.
Conversational AI for inbound B2B sales.