Hey folks,
I’m new to the AI automation game and trying to get my agency off the ground. But I’ve hit a snag with n8n’s workflow limits. It’s tough to grow when you’re capped at 10k executions a month, especially for chatbots. Even one client can eat that up fast!
The $50 monthly plan is out of my budget right now. But I need a way to serve multiple clients without breaking the bank. I’m not selling workflow executions directly. Instead, I want to offer chatbots and AI automation solutions where n8n runs things behind the scenes.
My goal is to build a scalable business with good profits. But these workflow limits are holding me back.
Has anyone else dealt with this? What tricks or tools have you used to scale up without spending a fortune? Any advice would be awesome!
Thanks guys!
hey soaringeagle, been there! have u considered using multiple free n8n accounts? it’s bit of hassle, but could work for now. another option is looking into open-source alternatives like huginn or apache nifi. they might not be as user-friendly, but no execution limits. good luck scaling ur biz!
I’ve faced similar challenges scaling my automation business. One approach that worked well for me was combining n8n with other tools to distribute the workload. For instance, I use n8n for core logic and API integrations, but offload high-volume tasks like chatbot interactions to dedicated platforms like Rasa or Botpress. This lets you leverage n8n’s strengths while avoiding execution limits.
Another strategy is to optimize your workflows. I’ve found that consolidating multiple steps and using efficient data processing can significantly reduce execution counts. It takes some refactoring, but it’s worth it.
Lastly, consider a hybrid model where you use n8n for prototyping and initial setup, then gradually migrate high-volume clients to a custom solution as you grow. This allows for flexibility while keeping costs manageable early on.
Remember, constraints often breed innovation. Use this as an opportunity to really hone your automation skills and create more efficient solutions.
Have you considered serverless platforms like AWS Lambda or Google Cloud Functions? They offer pay-per-execution models that could be more cost-effective for your use case. You could set up your core logic there and use n8n for orchestration or less frequent tasks.
Another approach is to implement caching strategies. By storing and reusing common responses, you can significantly reduce the number of workflow executions needed.
Don’t overlook the power of batching either. If possible, group multiple client requests into single workflow runs. This can dramatically cut down on execution counts.
Lastly, as you grow, look into building some custom components. While it requires more upfront work, it can pay off in the long run by reducing reliance on third-party tools and their limitations.
Remember, scaling often involves creative problem-solving. Keep experimenting and you’ll find a solution that works for your business model.