Make (ex-Integromat) is clearly behind n8n when it comes to building AI workflows and agents, including RAG. But does it mean that you can’t have highly reliable knowledge retrieval within your Make workflows?
Absolutely not!
Implementing reliable knowledge retrieval in Make
The implementation of robust RAG systems is extremely complex anyway: cleaning & formatting the incoming data, embedding pipeline, metadata, chunking methods, retrieval techniques…
This is where Lookio intervenes as the easiest solution to do AI-powered knowledge retrieval.
3 steps to get started once you’ve setup your workspace:
- Upload your resource documents (PDF, Docx, URLs, plain text…)
- Configure Assistants (context, output guidelines, resources access)
- Query your Assistants via API to automate retrieval
Lookio users like to call it “NotebookLM, but with an API”.
In Make, you’ll simply have to configure an API call module and follow the instructions provided by Lookio’s API docs, also directly available in the “API details” tab of your Assistants.
Top RAG use cases for Make automations
Primary use cases include SEO-focused content creation, support chatbots, and internal tools, though high-quality knowledge retrieval can be integrated into many additional business workflows.
It’s now your turn to get started and enjoy best-in-class RAG in your Make workflows! Create your free Lookio account and enjoy 100 free credits, no credit card required.
