Google Opal is one of the more interesting things Google Labs has shipped this year. You describe an AI workflow in natural language, drop a few blocks on a canvas, and get a running mini-app pointed at your Gmail, Drive, or Docs. The problem shows up the moment you try to publish anything. Opal cannot post to LinkedIn, X, or Instagram, cannot call an arbitrary webhook, and cannot run outside the Google Workspace fence. For a builder who wants their agent to actually do work, that is a wall.
If we hit that wall too, these seven Google Opal alternatives are where we would go next. They cover the range: fully open-source and self-hostable, cloud-native with generous free tiers, and AI-native platforms where an agent reasons over a task instead of following brittle if-this-then-that rules.
Quick comparison
| App | Best for | Free plan | Starting price/mo | Standout feature |
|---|---|---|---|---|
| n8n | Self-hosted power users | Unlimited on self-host | $24 (cloud) | Full JavaScript and Python nodes |
| Make | Visual workflows with branching | 1,000 ops | $10.59 | Cleanest visual editor of the bunch |
| Zapier | Widest integration list | 100 tasks | $19.99 | 8,000+ app connections |
| Activepieces | Open-source Zapier clone | 1,000 tasks | $10 | Free lifetime deals, no per-task caps on self-host |
| Gumloop | AI-native canvas builder | 1,000 credits | $97 | Purpose-built for LLM-heavy pipelines |
| Lindy | Agents that reason, not follow | 400 tasks | $49.99 | Natural-language agent spec |
| Power Automate | Microsoft 365 shops | Bundled with 365 | $15 | Desktop RPA plus cloud flows |
Why builders leave Google Opal
The complaint we hear most is publishing. Opal can draft a LinkedIn post, but it cannot post it. It can generate a report, but it cannot email it to a list that lives outside your Workspace. Every serious content or ops workflow eventually needs an outbound webhook, and Opal does not offer one.
The second complaint is portability. An Opal app lives inside your Google account. You cannot export the workflow to run it elsewhere, hand it off to a client, or version-control the definition. For a builder who thinks about handoff and reproducibility, that is a dealbreaker.
The third is model lock-in. Opal only talks to Gemini. Some tasks want Claude, some want a local Ollama model, some want a cheap open-weights model on Fireworks. Every alternative on this list lets you pick.
The alternatives
n8n — Best for teams that want to own the whole stack
n8n is the tool we reach for when the workflow needs to run for years and cannot go down when a vendor changes their pricing. The Community Edition is fair-code under the Sustainable Use License, free to self-host with no execution cap, and includes all 400-plus integrations plus full JavaScript and Python code nodes. You can drop into raw code any time the visual editor cannot express what you need.
Where it falls short: The self-hosted setup wants a real server, a database, and someone comfortable with Docker. The cloud plan is priced per execution, which gets pricey once you scale, and the editor is denser than Make or Zapier.
Pricing:
- Free: Unlimited executions on self-host, community edition
- Cloud: Starts at $24/mo for 5,000 executions
Migrating from Opal: No direct import. You rebuild the workflow node by node, but the mapping is intuitive if your Opal app is under a dozen steps.
Bottom line: Pick n8n if you plan to run this workflow for years and want zero vendor risk.
Make — Best for visual thinkers who want more than Zapier gives
Make (formerly Integromat) sits between Opal’s simplicity and n8n’s power. The canvas is the cleanest of any tool on this list, branching and error handling are first-class, and the pricing per operation is friendlier than Zapier for anything that fires more than a few times a day.
Where it falls short: Complex scenarios eat operations fast, and the debugging tools are shallower than n8n. Some enterprise integrations lag Zapier by a release or two.
Pricing:
- Free: 1,000 ops per month
- Paid: $10.59/mo Core plan for 10,000 ops
Migrating from Opal: No importer. Copy the logic manually. Make’s Google Workspace modules cover everything Opal exposes.
Bottom line: Pick Make if you want a visual editor that is nicer to look at than n8n but still has real branching.
Zapier — Best for teams that need to connect anything
Zapier is the tool with the widest integration surface, over 8,000 apps at last count. If your workflow touches a niche SaaS product, Zapier is the safest bet to have a working connector. The Interfaces and Tables products let you build small internal tools without leaving the platform.
Where it falls short: The per-task pricing is unforgiving at scale, and the free tier caps out at 100 tasks per month. Once a workflow becomes non-trivial, Zapier is often the most expensive option in the room.
Pricing:
- Free: 100 tasks per month
- Paid: $19.99/mo Starter plan for 750 tasks
Migrating from Opal: Rebuild manually. The Google Workspace triggers in Zapier are the most mature in the industry.
Bottom line: Pick Zapier when the workflow depends on an integration nobody else has.
Activepieces — Best open-source Zapier clone
Activepieces is the closest thing to Zapier’s simplicity in open-source form. The self-hosted version is free with no limits, the cloud plan gives 1,000 tasks per month free, and the piece framework is written in TypeScript, so extending it is straightforward for any web developer.
Where it falls short: The integration library is smaller than Zapier’s or n8n’s. Enterprise connectors that require complex OAuth flows are hit and miss.
Pricing:
- Free: 1,000 tasks per month cloud, unlimited self-hosted
- Paid: $10/mo for 5,000 tasks
Migrating from Opal: No importer. The clean node model makes rebuilds fast.
Bottom line: Pick Activepieces if you want Zapier’s feel without the bill, and you are comfortable maintaining a self-hosted instance.
Gumloop — Best for AI-heavy pipelines
Gumloop was built for the workflows Opal is trying to be. It is canvas-based, LLM-native, and every node assumes you are stitching together prompts, retrieval, and structured outputs. The company raised a $50 million Series B in early 2026 led by Benchmark, so the runway is not a worry.
Where it falls short: Pricing jumps steeply past the free tier. Non-AI integrations are thinner than the incumbents.
Pricing:
- Free: 1,000 credits per month
- Paid: $97/mo Starter for 30,000 credits
Migrating from Opal: No importer, but the mental model transfers cleanly. Gumloop’s flow nodes match Opal’s block canvas one-to-one for most cases.
Bottom line: Pick Gumloop if 80% of what you are building is prompt chains, retrieval, and LLM output shaping.
Lindy — Best when you want an agent instead of a flowchart
Lindy takes a different approach. You describe what you want in plain language (“read my inbox, draft replies to sales questions, book meetings on Fridays”) and Lindy assembles an agent that reads context and decides what to do. That works better than a rigid flowchart for messy real-world tasks like triaging support tickets or handling customer email.
Where it falls short: Agents are less predictable than deterministic flows. You will not know exactly what runs on every trigger, which spooks compliance teams.
Pricing:
- Free: 400 tasks per month
- Paid: $49.99/mo Pro for 5,000 tasks
Migrating from Opal: Rebuild as an agent brief, not a graph. This is a mental-model shift, not a copy job.
Bottom line: Pick Lindy for fuzzy, judgment-heavy tasks where a strict flow chart keeps breaking.
Microsoft Power Automate — Best if your company runs on Microsoft 365
Power Automate ships with most Microsoft 365 licenses at no extra cost, which changes the buy-or-build math for anyone already inside the Microsoft ecosystem. The desktop RPA piece is powerful enough to script legacy Windows apps, and the cloud flow builder handles Outlook, Teams, SharePoint, and Dynamics natively.
Where it falls short: The UI is dated, the licensing rules are notoriously tangled, and non-Microsoft integrations feel like second-class citizens.
Pricing:
- Free: Bundled with Microsoft 365 plans
- Paid: $15/mo per user for premium connectors
Migrating from Opal: Rebuild. The Outlook and Teams triggers are the strongest reason to bother.
Bottom line: Pick Power Automate when your company already pays for Microsoft 365 and the workflow lives inside Outlook, Teams, or SharePoint.
How to choose
Pick n8n if you want to own the whole stack and never worry about a vendor changing the terms. Pick Make if you want a nicer canvas than n8n without giving up branching. Pick Zapier when the workflow needs an integration only Zapier has. Pick Activepieces if you want the Zapier feel without the bill and can run a small server. Pick Gumloop when the job is mostly prompts and LLM stitching. Pick Lindy when the task is judgment-heavy and a strict flowchart keeps breaking. Pick Power Automate if your company already pays for Microsoft 365.
Stay on Opal when you are prototyping ideas, playing with Gemini, or the workflow lives entirely inside Google Workspace and never needs to talk to the outside world.
FAQ
Can Google Opal publish to social media? No. As of 2026 Opal cannot post to LinkedIn, X, Instagram, or any external social platform via API. This is the single biggest reason content creators leave for Make, Zapier, or n8n.
What is the cheapest Google Opal alternative? Self-hosted n8n or Activepieces, both free with no execution cap. On the cloud side, Activepieces gives 1,000 tasks per month free, matching Opal’s spirit without the Google Workspace fence.
Is there an open-source Google Opal alternative? Yes. n8n and Activepieces are both open-source and self-hostable. Both cover the workflow-automation piece Opal handles, with far more integrations and no vendor lock-in.
Can I use a non-Google model with these alternatives? Yes. n8n, Make, Zapier, Activepieces, Gumloop, and Lindy all support Claude, GPT, open-weights models, and self-hosted Ollama endpoints. Only Opal is locked to Gemini.
What do people use instead of Google Opal for AI agents? For agent-style flows, Lindy and Gumloop are the most-recommended alternatives on Reddit and Hacker News in 2026. For deterministic pipelines that just happen to call an LLM, n8n and Make dominate.
