This template processes a CSV of questions and returns an enriched CSV with RAG-based answers produced by your Lookio assistant.

Upload a CSV that contains a column named Query, and the workflow will loop through every row, call the Lookio API, and append a Response column containing the assistant's answer.

It's ideal for batch tasks like drafting RFP responses, pre-filling support replies, generating knowledge-checked summaries, or validating large lists of product/customer questions against your internal documentation.

Who is this for?

• Knowledge managers & technical writers: Produce draft answers to large question sets using your company docs.
• Sales & proposal teams: Auto-generate RFP answer drafts informed by internal docs.
• Support & operations teams: Bulk-enrich FAQs or support ticket templates with authoritative responses.
• Automation builders: Integrate Lookio-powered retrieval into bulk data pipelines.

What it does / What problem does this solve?

• Automates bulk queries: Eliminates the manual process of running many individual lookups.
• Ensures answers are grounded: Responses come from your uploaded documents via Lookio, reducing hallucinations.
• Produces ready-to-use output: Delivers an enriched CSV with a new Response column for downstream use.
• Simple UX: Users only need to upload a CSV with a Query column and download the resulting file.

How it works

1. Form submission: User uploads a CSV via the Form Trigger.
2. Extract & validate: Extract all rows reads the CSV and Aggregate rows checks for a Query column.
3. Per-row loop: Split Out and Loop Over Queries iterate rows; Isolate the Query column normalizes data.
4. Call Lookio: Lookio API call posts each query to your assistant and returns the answer.
5. Build output: Prepare output appends Response values and Generate enriched CSV creates the downloadable file delivered by Form ending and file download.

Why use Lookio for high quality RAG?

While building a native RAG pipeline in n8n offers granular control, achieving consistently high-quality and reliable results requires significant effort in data processing, chunking strategy, and retrieval logic optimization. Lookio is designed to address these challenges by providing a managed RAG service accessible via a simple API.

It handles the entire backend pipeline—from processing various document formats to employing advanced retrieval techniques—allowing you to integrate a production-ready knowledge source into your workflows. This approach lets you focus on building your automation in n8n, rather than managing the complexities of a RAG infrastructure.

How to set up

1. Create a Lookio assistant: Sign up at https://www.lookio.app/, upload documents, and create an assistant.
2. Get credentials: Copy your Lookio API Key and Assistant ID.
3. Configure the workflow nodes:
   • In the Lookio API call HTTP Request node, replace the api_key header value with your Lookio API Key and update assistant_id with your Assistant ID (replace placeholders like <your-lookio-api-key> and <your-assistant-id>).
   • Ensure the Form Trigger is enabled and accepts a .csv file.
4. CSV format: Ensure the input CSV has a column named Query (case-sensitive as configured).
5. Activate the workflow: Run a test upload and download the enriched CSV.

Requirements

• An n8n instance with the ability to host Forms and run workflows
• A Lookio account (API Key) and an Assistant ID

How to take it further

• Add rate limiting / retries: Insert error handling and delay nodes to respect API limits for large batches.
• Improve the speed: You could drastically reduce the processing time by parallelizing the queries instead of doing them one after the other in the loop. For that, you could use HTTP request nodes that would trigger your sort of sub-workflow.
• Store results: Add an Airtable or Google Sheets node to archive questions and responses for audit and reuse.
• Post-process answers: Add an LLM node to summarize or standardize responses, or to add confidence flags.
• Trigger variations: Replace the Form Trigger with a Google Drive or Airtable trigger to process CSVs automatically from a folder or table.