Quick overview This workflow watches a Google Drive folder for newly uploaded contract PDFs, extracts key clauses with Groq-hosted LLMs, compares them to standard clauses stored in Notion, generates a structured risk report and clause rewrites, sends a Slack alert for high-risk contracts, and saves the review to Notion. How it works Triggers when a new file is created in a specific Google Drive folder. Downloads the file and extracts text from it (using PDF text extraction when the uploaded file is a PDF). Uses a Groq-hosted LLM to extract key contract clauses (payment terms, penalties, SLA, termination, renewal, liability, and data protection) into structured JSON. Pulls the company’s standard clause library from Notion and compares each extracted vendor clause to the corresponding standard text. Uses a Groq-hosted LLM to generate a structured legal risk report with an overall risk level, executive summary, clause-by-clause risk review, missing protections, and negotiation recommendations. Rewrites medium- and high-risk clauses with a Groq-hosted LLM to produce negotiation-ready alternative wording aligned to the Notion standards.
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Google Drive
Groq Chat Model
NotionSlackRelated workflows
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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
Schedule weekly focus-time blocks with Google Calendar, OpenAI, and Slack
Quick overview This workflow runs every Sunday at 18:00 to scan your Google Calendar for next week, find free gaps of at least two hours within your working hours, auto-book them as “🧘 Focus Time” events, and then DM you a personalized deep-work plan in Slack using OpenAI. How it works Runs every Sunday at 18:00 on a schedule. Loads your working-hour preferences and fetches all events from your Google Calendar. Calculates weekday-only free gaps within your working hours and keeps only gaps that meet the minimum block length. If no qualifying gap exists, sends you a Slack DM warning that next week is too fragmented for a focus block. If gaps exist, limits the number of blocks for the week and creates “🧘 Focus Time (protected by n8n)” events in Google Calendar for each selected slot. Uses OpenAI to generate a short, personal Slack message that lists the protected blocks and suggests what kind of work fits each. Sends the generated deep-work plan to you as a Slack DM. Setup Add Google Calendar credentials, select the calendar to read from and the calendar to create “🧘 Focus Time” events in. Add Slack credentials and set your target Slack username in both the plan DM and warning mes
Recommend supplier consolidation with Google Sheets, Groq, Slack and Gmail
Quick overview This workflow runs weekly to read supplier spend data from Google Sheets, detect overlapping suppliers across departments, estimate potential consolidation savings, and use Groq-hosted LLM analysis to assess risk and produce recommendations that are sent to Slack and emailed via Gmail. How it works Runs every week on a scheduled trigger. Reads supplier records from a Google Sheets spreadsheet and keeps key fields like supplier name, department, spend, risk rating, and stakeholder email. Groups and normalizes supplier names to find suppliers used by multiple departments and calculates estimated savings and an opportunity level. Sends each consolidation opportunity to a Groq chat model to evaluate risk versus savings and return a JSON decision and recommendation. Parses the AI JSON output, merges it with the calculated savings data, and formats a final recommendation record. Posts the recommendation to a Slack channel and emails a formatted report to the supplier stakeholder email address. Setup Connect your Google Sheets OAuth account and update the spreadsheet ID and sheet/tab to match your supplier records. Add a Groq API credential for the chat model used to evalua