This article provides a complete, practical walkthrough of the Extractfromfile Form Automate Triggered n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Intermediate setup in 15-45 minutes. One‑time purchase: €29.

What This Agent Does

This agent orchestrates a reliable automation between HTTP Request, Webhook, handling triggers, data enrichment, and delivery with guardrails for errors and rate limits.

It streamlines multi‑step processes that would otherwise require manual exports, spreadsheet cleanup, and repeated API requests. By centralizing logic in n8n, it reduces context switching, lowers error rates, and ensures consistent results across teams.

Typical outcomes include faster lead handoffs, automated notifications, accurate data synchronization, and better visibility via execution logs and optional Slack/Email alerts.

How It Works

The workflow uses standard n8n building blocks like Webhook or Schedule triggers, HTTP Request for API calls, and control nodes (IF, Merge, Set) to validate inputs, branch on conditions, and format outputs. Retries and timeouts improve resilience, while credentials keep secrets safe.

Third‑Party Integrations

• HTTP Request
• Webhook

Import and Use in n8n

1. Open n8n and create a new workflow or collection.
2. Choose Import from File or Paste JSON.
3. Paste the JSON below, then click Import.
4. Show n8n JSON

   Title:
   Building an Automated Resume Review System with n8n, OpenAI, and Google Sheets
   
   Meta Description:
   Discover how to automate resume screening with n8n using OpenAI for AI-powered evaluation and Google Sheets for applicant tracking. Streamline your recruitment process with this end-to-end automated workflow.
   
   Keywords:
   n8n automation, resume review automation, AI HR tools, OpenAI GPT-4, Google Sheets integration, resume parsing, applicant tracking system, HR automation workflow, automate CV review, AI hiring tools
   
   Third-Party APIs and Services Used:
   
   1. OpenAI API (GPT-4o-mini) – For language-based tasks such as resume summarization, qualification extraction, and HR-style candidate evaluation.
   
   2. Google Drive API – To upload and store incoming resume PDFs securely.
   
   3. Google Sheets API – For storing structured extracted applicant information and score-based assessments in a spreadsheet for tracking and collaboration.
   
   4. LangChain (via n8n Langchain Nodes) – For structured extraction, summarization, and AI insights powered by OpenAI models.
   
   Article:
   
   Automating Resume Screening with n8n, OpenAI, and Google Sheets
   
   In today’s fast-paced hiring environment, HR teams are constantly looking for ways to streamline their hiring processes. Manual resume evaluation is time-consuming, error-prone, and often inconsistent. That’s where workflow automation platforms like n8n combined with AI tools like OpenAI come in. This article dives into an advanced resume review system built using n8n that automates end-to-end operations—from accepting CVs to scoring them and storing candidate data in an organized format.
   
   Let’s explore how this intelligent system works and how you can adopt a similar solution to save hours of manual labor and elevate your HR processes using automation.
   
   Overview: What Does the Workflow Do?
   
   This automated n8n workflow simplifies and enhances the HR recruiting pipeline. It performs the following key functions:
   
   1. Accepts resume submissions from a form.
   2. Uploads resume PDFs to Google Drive.
   3. Extracts structured personal and professional data using AI.
   4. Analyzes qualifications, job history, and skills.
   5. Generates an HR-style summary of the candidate.
   6. Scores and evaluates the candidate based on a desired job profile.
   7. Logs all data into Google Sheets for easy access and decision-making.
   
   Let’s break this down step by step.
   
   Step 1: Resume Submission via Web Form
   
   The workflow kicks off when an applicant submits their resume through a form powered by the n8n Form Trigger node. The form captures:
   
   - First Name
   - Last Name
   - Email Address
   - Resume File (PDF only)
   
   Bot traffic is ignored, and data attribution is disabled to maintain clean inputs.
   
   Step 2: Resume Upload to Google Drive
   
   Once submitted, the resume PDF is uploaded to a specified folder in Google Drive using the Google Drive node. File names are timestamped with the submission date to maintain organizational clarity.
   
   Step 3: Text Extraction from PDF
   
   Next, the workflow uses the Resume Extraction node to automatically extract text from the uploaded PDF. This is vital for enabling AI-based parsing in subsequent steps.
   
   Step 4: AI-Powered Data Extraction
   
   Now powered by OpenAI through n8n's integration with LangChain nodes, the system uses advanced LLM models to intelligently extract structured information from the resume text. Two major types of data are retrieved:
   
   - Personal Information: Name, email, phone number, birthdate, LinkedIn, city, and website.
   - Professional Data: Educational qualifications, job history summary, and a list of technical skills.
   
   This not only streamlines parsing but ensures that crucial hiring data is interpreted and normalized for downstream processing.
   
   Step 5: Merging & Summarization
   
   The extracted data is merged using n8n's Merge node. The result is passed to the Summarizer node, where OpenAI generates a concise, professional summary of the candidate’s profile. The summary highlights location, education, experience, and skills—all written in under 100 words for quick evaluation by HR.
   
   Step 6: Role Matching & Candidate Scoring
   
   With the summary ready, the candidate profile is fed into the HR Expert node, which compares it to a predefined "ideal candidate" template. In this case, the profile is for an Automation Expert skilled in n8n, Python, and workflow design, preferably based in Northern Italy.
   
   The AI generates:
   
   - A score from 1 to 10 indicating how well the candidate matches the role.
   - A “consideration” field explaining the reasoning behind the given score.
   
   This effectively mimics an HR specialist reviewing a resume, but at scale and instantaneously.
   
   Step 7: Data Logging to Google Sheets
   
   Finally, all structured applicant data—including names, contact info, skills, experience, summary, score, and comments—is recorded into a Google Sheet for tracking, collaboration, and decision-making.
   
   The sheet contains columns like:
   
   - First Name / Last Name
   - City, Email
   - Educational Qualification
   - Job History
   - Skills
   - AI Summary
   - Score (Vote)
   - Reason for Consideration
   - Applied Date
   
   Key Benefits of This System
   
   ✅ Saves Time:
   Manual HR screening can take minutes (or even hours) per resume. This system processes resumes within seconds.
   
   ✅ Reduces Human Bias:
   Using OpenAI ensures a consistent evaluation across candidates, with HR scoring based purely on set criteria.
   
   ✅ Centralized Data:
   Google Sheets integration makes it easy to filter, review, and share candidate information across teams.
   
   ✅ Scalable:
   Whether processing one resume or 1,000, the system functions just the same—no bottlenecks.
   
   ✅ Customizable:
   You can easily update job role profiles, qualification extraction schemas, or pipeline steps directly in n8n.
   
   Conclusion
   
   This resume review workflow is a shining example of what’s possible when you combine no-code/low-code automation with AI-powered tools like OpenAI and robust data platforms like Google Sheets. Built using n8n, this system eliminates HR drudgery while enhancing consistency and efficiency in hiring.
   
   Whether you're a tech recruiter in a fast-growing agency or an HR operations manager in a startup, leveraging n8n workflows like this can revolutionize your hiring funnel. Ready to reimagine how your team handles resumes? Start building with n8n and make your HR processes intelligent and scalable.
   
   — End —

5. Set credentials for each API node (keys, OAuth) in Credentials.
6. Run a test via Execute Workflow. Inspect Run Data, then adjust parameters.
7. Enable the workflow to run on schedule, webhook, or triggers as configured.

Tips: keep secrets in credentials, add retries and timeouts on HTTP nodes, implement error notifications, and paginate large API fetches.

Validation: use IF/Code nodes to sanitize inputs and guard against empty payloads.

Why Automate This with AI Agents

AI‑assisted automations offload repetitive, error‑prone tasks to a predictable workflow. Instead of manual copy‑paste and ad‑hoc scripts, your team gets a governed pipeline with versioned state, auditability, and observable runs.

n8n’s node graph makes data flow transparent while AI‑powered enrichment (classification, extraction, summarization) boosts throughput and consistency. Teams reclaim time, reduce operational costs, and standardize best practices without sacrificing flexibility.

Compared to one‑off integrations, an AI agent is easier to extend: swap APIs, add filters, or bolt on notifications without rewriting everything. You get reliability, control, and a faster path from idea to production.

Best Practices

• Credentials: restrict scopes and rotate tokens regularly.
• Resilience: configure retries, timeouts, and backoff for API nodes.
• Data Quality: validate inputs; normalize fields early to reduce downstream branching.
• Performance: batch records and paginate for large datasets.
• Observability: add failure alerts (Email/Slack) and persistent logs for auditing.
• Security: avoid sensitive data in logs; use environment variables and n8n credentials.

FAQs

Can I swap integrations later? Yes. Replace or add nodes and re‑map fields without rebuilding the whole flow.

How do I monitor failures? Use Execution logs and add notifications on the Error Trigger path.

Does it scale? Use queues, batching, and sub‑workflows to split responsibilities and control load.

Is my data safe? Keep secrets in Credentials, restrict token scopes, and review access logs.