Airtable and Vector Store Tool integration

Are you a popular tech startup accelerator (named after a particular higher order function) overwhelmed with 1000s of pitch decks on a daily basis? Wish you could filter through them quickly using AI but the decks are unparseable through conventional means? Then you're in luck! This n8n template uses Multimodal LLMs to parse and extract valuable data from even the most overly designed pitch decks in quick fashion. Not only that, it'll also create the foundations of a RAG chatbot at the end so you or your colleagues can drill down into the details if needed. With this template, you'll scale your capacity to find interesting companies you'd otherwise miss! Requires n8n v1.62.1+ How It Works Airtable is used as the pitch deck database and PDF decks are downloaded from it. An AI Vision model is used to transcribe each page of the pitch deck into markdown. An Information Extractor is used to generate a report from the transcribed markdown and update required information back into pitch deck database. The transcribed markdown is also uploaded to a vector store to build an AI chatbot which can be used to ask questions on the pitch deck. Check out the sample Airtable here: https://airtable.com/appCkqc2jc3MoVqDO/shrS21vGqlnqzzNUc How To Use This template depends on the availability of the Airtable - make a duplicate of the airtable (link) and its columns before running the workflow. When a new pitchdeck is received, enter the company name into the Name column and upload the pdf into the File column. Leave all other columns blank. If you have the Airtable trigger active, the execution should start immediately once the file is uploaded. Otherwise, click the manual test trigger to start the workflow. When manually triggered, all "new" pitch decks will be handled by the workflow as separate executions. Requirements OpenAI for LLM Airtable For Database and Interface Qdrant for Vector Store Customising This Workflow Extend this starter template by adding more AI agents to validate claims made in the pitch deck eg. Linkedin Profiles, Page visits, Reviews etc.

What this workflow does Are you a leading tech accelerator (named after a higher-order function) buried under thousands of pitch decks daily? Struggling to quickly identify the next big startup because these decks are too design-heavy for traditional parsing tools? You’re in luck! This n8n template leverages multimodal LLMs to efficiently extract key information from even the most intricate pitch decks. Not only does it analyze content at scale, but it also builds the foundation for a RAG chatbot—so you and your team can explore deeper insights at any time. With this solution, you’ll never miss the hidden gems again! Requirements n8n v1.62.1+ OpenAI (for LLM) Airtable (as the pitch deck database) Qdrant (for the vector store) How It Works Airtable serves as the pitch deck repository, where uploaded PDFs are stored. An AI Vision model transcribes each PDF page into markdown. The markdown is processed by an Information Extractor, which generates a summary and updates key fields in Airtable. The markdown content is also indexed into Qdrant, creating a searchable AI chatbot that lets you interact with the pitch deck data. 📋 Sample Airtable: View Example Here How To Use Duplicate the Airtable: Use the template above to create your own Airtable with the same structure. Upload a Pitch Deck: Add the company name in the Name column and upload the PDF into the File column. Leave other fields blank. Trigger Workflow: If the Airtable trigger is enabled, the workflow starts automatically when a new file is uploaded. You can also manually trigger the workflow to process any "new" pitch decks in bulk. Each pitch deck will be processed individually in separate executions. Customization Ideas Enhanced Validation: Add agents to verify claims from pitch decks (e.g., LinkedIn profiles, website traffic, product reviews). Tailored Reports: Modify the extraction logic to generate customized reports for your accelerator’s needs. Chatbot Extensions: Use the chatbot to compare multiple startups, filter based on specific criteria, or surface competitor insights. With this template, you’ll scale your ability to uncover promising startups—turning overwhelming data into actionable insights in no time!