Quick overview This workflow receives a webhook with either a URL or raw text, uses Groq (Llama 3.3 70B) to analyze and repurpose the content into Instagram, X, LinkedIn, email, and video formats, optionally logs results to Google Sheets, and posts the LinkedIn text to multiple platforms via Upload-Post.com. How it works Receives a POST webhook request containing a single content value that is either a URL or plain text. If the input starts with http, it fetches the page content over HTTP and packages it as cleaned source text; otherwise it uses the provided text as-is. Sends the prepared content to Groq (Llama 3.3 70B) to generate a structured analysis of the core message, key points, audience, tone, and hook angles. Uses Groq again to generate platform-specific outputs (Instagram caption/hashtags, X thread, LinkedIn post, email newsletter, and a short video script) as JSON. Parses the AI JSON, validates character limits for Instagram, LinkedIn, and X, and returns an error response if the output cannot be parsed.
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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
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
Score and triage inbound leads with Groq, Slack, Google Sheets, and Google Tasks
Quick Overview This workflow captures leads via an n8n form, stores them in an n8n Data Table, uses a Groq Llama 3.3 chat model to score and categorize each lead and draft a reply, optionally alerts in Slack and creates a Google Task, and writes the results back to the Data Table. How it works Receives a new lead submission through an n8n Form trigger (name, email, company, source, and message). Saves the submitted lead into an n8n Data Table and keeps only the fields needed for scoring. Sends the lead details to a Groq Chat Model via an AI Agent to generate a JSON response with a score (1–100), tier (Hot/Warm/Cold), and a suggested reply. Uses the AI Agent’s tool actions to post an alert to Slack and create a task in Google Tasks only when the lead’s score is above the defined threshold. Parses the AI Agent output as JSON and updates the original Data Table row with the generated score, tier, and reply. Setup Configure the n8n Form trigger and embed or share its URL where you collect leads. Create or select an n8n Data Table for leads and ensure it includes columns for score, tier, reply, and an id used to match rows during updates. Add a Groq API credential and select the Groq ch