Does Jorbly Use AI or Scraping to Keep Jobs Current?

Does Jorbly Use AI or Scraping to Keep Jobs Current?

Short answer: Yes — but with intention, transparency, and a commitment to quality.

In the world of job boards, automation is essential. But how you use it differentiates noise from clarity. At Jorbly, we use a hybrid system combining intelligent scraping, rule-based validation, and human oversight — all aligned with our mission: real jobs, direct connections, always fresh.

🧰 How Jorbly Keeps Jobs Fresh: The Hybrid Model

1. Smart Scraping (Crawler Infrastructure)

We periodically crawl employer career pages and verified job listings across technology, gaming, biotech, finance, manufacturing, defense, and more. These crawlers capture new roles, updates, and removals.

• We use carefully tuned scraping logic (not blunt, broad web scraping) to fetch structured job data.

• The scraper respects canonical job posting endpoints (career APIs, sitemap structures, etc.) rather than grabbing from noisy aggregates.

2. Rule-Based Filters & Validation

After scraping, listings go through filters to weed out:

• Duplicate posts

• Old or expired roles

• Listings lacking critical data (company link, title, location)

If a listing fails validation, we don’t include it in the public feed.

3. AI-Assisted Matching & Cleanup

We incorporate AI / ML in ways such as:

• Text normalization — standardizing job titles, roles, locations

• De-duplication models — detecting when the same role appears under slightly varied descriptions

• Ranking & relevance scoring — determining which roles should surface higher in filtered results

The AI layer helps maintain consistency, surface the best matches, and flag suspicious postings for review.

4. Scheduled Scrub & Pruning

On a regular cadence (daily or weekly), we:

• Mark roles as stale if their source page disappears or changes drastically

• Remove or hide listings that fail validity checks

• Re-crawl the employer’s page to fetch fresh updates
  

This ensures job cards aren’t left lingering long after they’ve been filled or removed.

5. Human Oversight & Spot Review

Automation is powerful — but it’s not perfect. We employ:

• Spot checks to sample listings and confirm authenticity

• Employer feedback loops so companies can flag or correct their own listings

• User reports — if a candidate finds a dead link or bad listing, we take it down quickly
  

This human layer catches edge cases and preserves trust in Jorbly’s feed.

🔍 Why This Approach Matters

1. Accuracy Over Volume Many platforms bulk-scrape and flood their feeds with stale, duplicate, or spam listings. We choose fewer, more accurate roles rather than more, lower-quality ones.
   

2. Direct-to-Employer Integrity Because we fetch from verified company sources (not aggregator sites), the listings maintain the direct link model — no recruiter intermediaries, no redirects.
   

3. Transparency & Trust We’re clear about how the system works — you’ll never see “AI curated” as an excuse for stale content. We back up automation with accountability.
   

4. Scalability Across Industries Our hybrid model supports breadth: gaming, AI, biotech, finance, defense — each with domain-specific rules and filters to maintain relevance in every vertical.
   

5. Reduced Noise, Improved UX By filtering proactively, candidates avoid “zero result” searches or broken links. The interface feels responsive, real, and instantly valuable.

✅ In Summary

Yes — Jorbly uses scraping combined with AI and rule-based validation to keep our job listings current, accurate, and meaningful. But more importantly, we do it smartly:

• We scrape from verified employer sources

• We validate, filter, and prune listings rigorously

• We employ AI for consistency, de-duplication, and relevance

• We add human oversight to catch what automation misses

The result? A clean, reliable job feed you can trust — across tech, gaming, biotech, finance, and more — without the noise or spam of traditional platforms.

Does Jorbly Use AI or Scraping to Keep Jobs Current?