Description This workflow automates document processing using LlamaParse to extract and analyze text from various file formats. It intelligently processes documents, extracts structured data, and delivers actionable insights through multiple channels. How It Works Document Ingestion & Processing 📄 Monitors Gmail for incoming attachments or accepts documents via webhook Validates file formats against supported LlamaParse extensions Uploads documents to LlamaParse for advanced text extraction Stores original documents in Google Drive for reference Intelligent Document Analysis 🧠 Automatically classifies document types (invoices, reports, etc.) Extracts structured data using customized AI prompts Generates comprehensive document summaries with key insights Converts unstructured text into organized JSON data Invoice Processing Automation 💼 Extracts critical invoice details (dates, amounts, line items) Organizes financial data into structured formats Calculates tax breakdowns, subtotals, and payment information Maintains detailed records for accounting purposes Multi-Channel Delivery 📱 Saves extracted data to Google Sheets for tracking and analysis Sends concise summaries via Telegr
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Gmail
Google Drive
Google SheetsWHTTP Request
OpenAI Chat ModelRelated workflows
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Quick overview This workflow monitors a Google Drive folder for newly uploaded invoice files, extracts text with OCR.Space, uses Google Gemini to convert the OCR text into structured invoice fields, validates required values, then stores results in Google Sheets and sends Gmail notifications for success or manual review. How it works Triggers when a new file is created in a specified Google Drive folder. Downloads the uploaded invoice file from Google Drive and checks that the MIME type is PDF, JPG, JPEG, or PNG. Sends the file to the OCR.Space API to extract the invoice text and stops if OCR reports a processing error. Uses Google Gemini to convert the OCR text into structured JSON containing supplier, invoice metadata, amounts, currency, and line items. Validates and normalizes the extracted fields, flags missing required values, and marks the record for manual review when needed. If manual review is required, sends a Gmail alert listing missing fields; otherwise, appends key invoice fields to Google Sheets and sends a Gmail confirmation email. Setup Connect Google Drive OAuth2 credentials and set the folder ID to watch for invoice uploads. Provide an OCR.Space API key and ensure
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Extract Twilio voice donation details with Groq, Gemini, and Google Sheets
Quick overview This workflow receives Twilio call recording callbacks, transcribes the audio with Groq Whisper, uses Google Gemini/Groq LLMs to extract structured donation details, and appends the results (with transcript and review flag) to Google Sheets. How it works Receives a Twilio Recording Status Callback webhook and immediately responds with TwiML (``). Captures call metadata (CallSid, caller number, recording URL/SID, and duration) and continues only if the recording exists and is at least 2 seconds long. Waits briefly for Twilio to finalize the media, then downloads the recording MP3 using Twilio HTTP Basic Auth. Sends the audio file to Groq’s Whisper transcription endpoint to generate a text transcript. Uses a LangChain prompt with Google Gemini and Groq chat models to extract donation amount, fee (if mentioned), beneficiary name, currency, a needs-review flag, and a short summary from the transcript. Parses the model output as JSON and falls back to an error summary with needs_review=yes if parsing fails. Checks Google Sheets for an existing row matching the CallSid/RecordingUrl and, if not found, appends a new row with the extracted fields, transcript, and call details