Quick overview This workflow receives loan applications via webhook, uses Anthropic Claude to verify document text and generate an underwriting recommendation, calculates an explainable risk score in code, logs each application to Google Sheets, and sends decision emails through SendGrid before returning a JSON response. How it works Receives a loan application via a POST webhook, including applicant details and extracted text from ID, income proof, and bank statement documents. Uses Anthropic Claude to extract key fields from the documents and cross-checks them against the applicant’s declared name, employer, and income to produce a verification score and inconsistency list. Stops early and returns a “Documents Insufficient” webhook response when the verification score is below the threshold. Calculates verified income, estimated monthly installment, debt-to-income and loan-to-income ratios, and a weighted 0–100 risk score and tier from credit score, ratios, employment tenure, bank health, and document consistency.
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Send a daily AI-ranked job match digest with Anthropic and Gmail from 6+ boards
Quick Overview This workflow runs every morning to pull jobs from multiple free job boards (and optional Adzuna), filters and de-duplicates results, scores each role against your resume and preferences using Anthropic, then emails a ranked digest via Gmail. How it works Runs every morning at 08:00 using a schedule trigger. Builds a list of job board API URLs (RemoteOK, Remotive, Arbeitnow, Jobicy, Himalayas, TheMuse, and optional Adzuna) based on your search settings. Fetches job listings from each board over HTTP. Normalizes all responses into a single job format, applies your filters (title keywords, tags, locations/remote, salary, and excluded terms), and de-duplicates roles across boards. Sends your resume, preferences, and the short-listed jobs to an Anthropic-powered AI agent to return a structured fit score, fit reason, risk/concerns, and a tailored first-person pitch for each job. Keeps only roles at or above your minimum score, ranks them by score, and generates an HTML email digest with links and source board attribution. Sends the digest to your target address using Gmail. Setup Add an Anthropic API credential, select an Anthropic chat model, and keep the structured outp
Chat with Google Docs and Sheets using a Claude AI agent
Quick Overview This workflow opens an n8n chat interface where an AI agent powered by Anthropic Claude answers questions by reading a connected Google Doc and/or Google Sheet on demand, using short-term conversation memory for follow-up questions. How it works Receives a user question through n8n’s built-in chat trigger. Uses an AI agent powered by Anthropic Claude to decide whether it needs to consult Google Docs, Google Sheets, or both. Reads the full text of the configured Google Doc when the question is about document content. Fetches rows from the configured Google Sheet tab when the question is about spreadsheet data. Answers in the chat based only on the retrieved Doc/Sheet content (or states the information isn’t present), while keeping the last 10 messages in memory for contextual follow-ups. Setup Add credentials for Anthropic (Claude), Google Docs, and Google Sheets. Replace YOUR_GOOGLE_DOC_ID_OR_URL with your target Google Doc URL or ID. Set the Google Sheet document ID and choose the tab (sheet name) to read in the Google Sheets tool. Confirm the connected Google account has access to both the Doc and the Sheet, then open the workflow chat and start asking questions.
Run AI employee onboarding with Groq, Google Workspace, and Gemini
Quick overview This workflow ingests onboarding documents from Google Drive into an in-memory vector store with Google Gemini embeddings, then runs a multi-channel onboarding chatbot powered by Groq, sends role-based welcome emails via Gmail when a new hire appears in Google Sheets, and schedules day 1/7/30 check-in emails. How it works Manually runs an ingestion flow that lists files in a specified Google Drive folder, downloads them, extracts text, and indexes them into an in-memory vector store using Google Gemini embeddings. Receives employee questions via n8n Chat (and optionally Slack or Telegram), normalizes the message into a single format, and rejects empty or overly long inputs. Uses a Groq LLM agent with per-user session memory to retrieve relevant excerpts from the in-memory company_docs knowledge base and generate a grounded answer, or directs the user to HR when no relevant content is found. Routes the assistant’s response back to the originating channel (n8n Chat, and optionally Slack or Telegram). Triggers every minute on updates to a Google Sheets “Hires” sheet, validates rows marked as Hired, and skips hires already present in the “Tracking” sheet. Builds a depart