The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Back to feedPost
AI Hiring Workflow & Candidate Automation System
I built an end‑to‑end AI‑powered hiring workflow that automates the entire candidate lifecycle — from screening to onboarding. This system replaces manual review, inconsistent communication, and slow decision‑making with a clean, structured, and fully automated pipeline.
What it does:
• Screens resumes and applications with role‑specific criteria
• Extracts skills, experience, and red flags automatically
• Generates structured candidate summaries for fast review
• Automates candidate communication and follow‑ups
• Schedules interviews and routes candidates to the right stage
• Delivers onboarding steps and training materials automatically
Why it matters:
Hiring is one of the most chaotic operational areas for most teams. This system turns it into a predictable, auditable workflow that saves hours per week and improves candidate experience.
Tech used:
AI models, embeddings, workflow automation (n8n), async operations, secure data handling, custom scoring logic.
Outcome:
A fast, fair, and scalable hiring pipeline that reduces time‑to‑hire, improves clarity, and eliminates repetitive manual work.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Related posts
Agentic AI Workflow for Real Estate Lead Enrichment (USA)
I built a production-grade, engineering-first workflow that turns minimal “clues” (company name, property address, or Tax ID) into a structured owner/contact dossier.
Stack: self-hosted n8n, OpenAI (GPT-5), Airtable (UI + database), Google Search, RealTrack (closed system)
Input → Output: 1–3 clues in → a complete enriched profile in ~60–120 seconds (with citations/links to sources) ready for sales outreach and due diligence.
The Problem (How the team worked before)
The client’s manual process looked like “crossfire research”:
- Find a company name + street / Tax ID
- Open multiple platforms/tabs
- Cross-check signals, collect evidence
- Compile a dossier in spreadsheets/CRM
This was slow (20–45 minutes per request), error-prone, and hard to scale.
I delivered an end-to-end agentic workflow that automates the same multi-platform research the team did manually — but faster and with consistent formatting.
1. ~90% reduction in pre-call research time per lead
2. ~60–120 seconds per lookup vs 20–45 minutes manually
3. ~$0.02 per enrichment request (token cost; excluding optional external services)
4. Self-hosted n8n: dramatically lower operational costs vs cloud pricing at scale
Amazing job Oleh!
I'll be honest — my last three posts flopped.
Took me a minute to see why. I'd been writing hot takes when I should've been writing what actually helps.
Here's a small automation I shipped last week that none of my "big" posts will beat for value:
A client kept losing meeting notes. Calls in Google Meet, transcripts in their inbox, action items nowhere. Standard SMB chaos.
The fix:
Google Meet transcript → n8n webhook → GPT extracts action items + owner → posts to their Slack channel + appends to a Notion database.
Now every meeting ends with a clean action list, automatically assigned. They stopped using the word "follow-up" in calls.
Not glamorous. Not contrarian. Just useful.
What's the smallest automation that made the biggest difference in YOUR work? Drop it below — I'm collecting ideas for clients. 👇
#n8n #Automation #Productivity
I built Travero: Commute as a smaller,
sharper version of the original Travero idea.
Travero started as an app for seeing weather along your driving route, based on where you’ll actually be at each point of the trip. That works really well for longer drives, but I kept thinking there’s a more frequent use case hiding inside it: the daily commute.
Most people don’t need a full navigation app every morning. They already know where they’re going. What they need is a quick answer before leaving:
Is traffic bad? Is there an incident? Will weather affect the drive? Should I leave now or wait a bit?
So Travero: Commute became a more focused product around that exact moment.
The app is built around saved Home and Work locations, one-tap commute checks, traffic status, incidents, weather along the route, alternative routes, and quick summaries that are easy to understand before you get in the car.
One important shift was treating weather as a supporting layer, not the main feature. For commute, traffic is the real priority. Weather still matters, but only when it affects the route.
I also wanted the app to feel more like a daily habit than a trip planner. Something you can open quickly in the morning or after work, check the route, and decide whether to leave now, wait, or take another way.
This project was a good reminder that sometimes the best product direction comes from narrowing the idea, not adding more features.
Travero: Commute is still part of the same bigger Travero vision, but with a much clearer daily use case.
Awesome work👏🔥🔥
Trending
Claude
Claude has entered the design space. How are you using Claude Design?
Contra University
Learn from expert creatives how to earn more using next-gen AI tools.
creativeaiflow
Creative AI workflows are evolving. What tools do you use, and what are their strengths and weaknesses?
portfolioreview
The best portfolios tell a story, not just show a grid. Share yours for feedback.
freelancerlife
Freelancer life is wins, pivots, and everything in between. What’s yours right now?