Quick overview This workflow receives a company name via webhook, runs three Tavily web searches (company info, recent news, and key people), uses Groq (Llama 3.3 70B) to synthesize a structured lead profile, optionally appends the results to Google Sheets, and returns the enriched profile in the webhook response. How it works Receives a POST webhook request containing a company name and an optional domain. Queries the Tavily Search API for company overview details, then searches Tavily again for recent news and key executives/leadership. Sends the combined search results to a Groq LLM agent to generate a sales-ready lead enrichment profile as strict JSON (company details, products, signals, news, pain points, and outreach angles). Parses the AI output, extracts valid JSON if possible, and flattens key fields into a single row-friendly structure. If parsing succeeds, appends the enriched lead data to a Google Sheets spreadsheet and returns the full profile in the webhook response. If parsing fails, returns an HTTP 422 error response with the raw AI output for troubleshooting. Setup Create a Groq API key, add it as an n8n Groq credential, and select it in the Groq LLM node.
Tags
Google Sheets
Groq Chat ModelWHTTP RequestRelated workflows
See all AI Automation→
Route procurement helpdesk tickets from Gmail with Groq and Slack
Quick Overview This workflow monitors a Gmail inbox for procurement requests, uses Groq (Llama 3.1) to classify and route each ticket with SLA logic, escalates high-risk items to Slack, creates a ticket via HTTP, sends an auto-reply from Gmail, and logs the full record to Google Sheets. How it works Triggers every minute when a new email arrives in a Gmail inbox. Extracts the sender, subject, body, timestamps, and Gmail thread/message IDs, and generates a procurement ticket ID. Looks up the email thread ID in Google Sheets to identify whether the request already exists. Uses Groq (Llama 3.1) to classify the request (category, urgency, sentiment, risk, team) and applies routing rules to set SLA deadlines, queues, and escalation flags. If escalation is required, posts a detailed alert to a Slack channel and creates an escalated ticket via an HTTP request; otherwise, creates a standard ticket via an HTTP request. Generates a short agent-facing status summary with Groq, emails the customer an acknowledgement and suggested reply via Gmail, and appends the full ticket and AI outputs to Google Sheets. Setup Connect your Gmail OAuth2 credential for both the inbox trigger and the customer a
Find and verify business emails with ScraperCity, OpenAI, Google Sheets, and Gmail
Quick overview This workflow reads contacts from Google Sheets, finds and verifies their business emails via the ScraperCity Email Finder API, generates a short personalized icebreaker with OpenAI, appends the enriched leads to another Google Sheet, and emails a run summary via Gmail. How it works Starts manually to run an email enrichment job. Reads contacts (first name, last name, domain) from an input Google Sheets worksheet and aggregates them into a single payload. Submits the contacts to the ScraperCity Email Finder API, then waits and repeatedly checks the job status until it succeeds or fails/times out. When the job succeeds, downloads the result CSV from ScraperCity, parses it, normalizes key fields (name, domain, email, verification status, provider), and keeps only rows with an email. For each verified contact, prompts OpenAI to generate one short, company-referencing cold-email opening line in the configured language. Appends the enriched lead (including email, status, and icebreaker) to an output Google Sheets worksheet and sends a summary email via Gmail. Setup Create a ScraperCity account with Email Finder credits and add an HTTP Header Auth credential that sends you
WGenerate weekly Pinterest content opportunity briefs with Apify, OpenAI and Google Sheets
Quick overview Research a Pinterest niche with FetchCat's Pinterest Search Scraper, preserve every source pin in Google Sheets, and use one evidence-controlled OpenAI call to identify recurring themes, underrepresented angles, and five production-ready content briefs without claiming search volume or trend growth. How it works Starts manually with one research niche and one to five exact Pinterest search phrases, plus locale, country, and a configurable result limit. Runs fetch_cat/pinterest-search-scraper through a Cloud-compatible HTTP Request and collects 20 to 500 public pins per search with public detail enrichment enabled. Validates, normalizes, and deduplicates returned pins. It stops before AI or destination writes when fewer than ten usable pins remain. Builds stable Google Sheets rows, deterministic phrase counts, and a bounded evidence packet, then uses one structured gpt-5.4-mini request for analysis. Removes invalid pin citations and rejects any finding that retains no supplied evidence, preventing unsupported recommendations from reaching the destination. Upserts source pins and a readable brief into separate Pins and Research Brief tabs using stable same-day research