AI Recruiter Copilot n8n Workflow: Mistral + Supabase Webhooks

Turn recruiter intake into structured jobs and candidate scoring—automatically

This AI Recruiter Copilot n8n Workflow uses Mistral AI and Supabase/PostgreSQL webhooks to automate three core recruiting tasks: job creation, resume intake & parsing, and a recruiter copilot chat that answers questions against stored candidate and job data.

What this workflow does

The workflow exposes recruiter webhooks and routes incoming requests based on the payload:

• Recruiter Intake Webhook (POST): receives recruiter payloads and validates required fields.
• Job creation (no resume file): uses Mistral AI to generate a structured job description and a skills list, then runs a Mistral AI bias/quality audit with up to two improvement cycles before publishing the approved job to Supabase.
• Resume processing (resume file attached): validates the upload is a PDF, extracts and cleans the resume text, and enriches it with candidate details from the webhook body.
• Structured candidate profile + embedding: uses Mistral AI to parse the resume into a structured candidate profile and generates a Mistral embedding for the resume text.
• Store in Supabase: upserts the candidate, updates stored resume text and vector embedding, and creates an application record linked to the supplied job_id.
• Optional candidate scoring: if job_id is provided, fetches the job from Supabase, scores the candidate against the job with Mistral AI, calculates a weighted match score, saves scoring fields back to the application, and returns a JSON response.
• Recruiter Copilot chat webhook: receives separate copilot chat requests via a second webhook for interactive recruiting Q&A.

Use cases

• Build a webhook-driven recruiting pipeline that creates jobs and ingests PDFs from external ATS forms.
• Automatically generate and audit job descriptions with Mistral AI, then store and reuse them in Supabase.
• Score candidates against specific job requirements and return results to your front-end in JSON.
• Give recruiters a “copilot” chat interface backed by stored job/candidate data and Mistral-generated embeddings.

Technical details

• AI: Mistral AI for job description generation, resume parsing, embeddings, Q&A, and bias/quality audit (up to two improvement cycles).
• Database: Supabase/PostgreSQL for jobs, candidates, applications, scores, and chat logs.
• n8n nodes/workflow logic: webhook, if, switch, merge, code, postgres.