Smart 3-stage extraction. Natural Hebrew optimization. System that learns from 0 real extractions.
Extract, translate, and format supplier catalogs into Hebrew Shopify listings—in minutes, not days.
Watch Katalyst turn a supplier link into a complete, SEO-ready Hebrew listing
Manual data entry doesn’t just cost time - it costs sales. Every hour spent copy-pasting is an hour a product isn't live and selling.
Problem 1: Time Drain
Onboarding a single product takes 15-30 minutes of copying specs and writing descriptions. For a 1,000-product catalog, that’s over 250 hours of tedious work - a bottleneck that directly delays revenue.
0+
Hours to list 1,000 products
Problem 2: Costly Errors
Manual data entry has up to a 4% error rate. A wrong spec or bad translation can lead to customer complaints and returns, with 40% of shoppers returning items due to poor product info.
0%
of shoppers return items due to bad data
Problem 3: Invisibility
53% of all e-commerce traffic comes from organic search. Without proper, localized SEO metadata for every product, you’re missing out on over half your potential customers.
0%
of traffic comes from search
Problem 4: Awkward Localization
A direct, robotic translation into Hebrew alienates customers. 65% of consumers prefer content in their native language. Nuance is critical for trust and conversions.
0%
of users prefer their native language
Watch Katalyst transform your product data in real-time. From upload to live products in minutes, not hours.
Provide a CSV of products, paste a list of URLs, or upload PDF spec sheets. That's all the AI needs.
Katalyst extracts all specs, writes compelling marketing copy in natural Hebrew, and handles SEO fields.
Review the AI-generated data, make any final tweaks, and publish directly to Shopify or download a ready-to-upload CSV.
Katalyst isn't just an extractor. It's a suite of AI tools designed to handle every part of the product onboarding process.
Pulls data from unstructured PDFs, supplier websites, and even basic CSV files, understanding context like a human would.
Goes beyond literal translation to generate natural, marketing-focused Hebrew while intelligently preserving English technical terms.
Automatically generates SEO-optimized titles, descriptions, and tags, plus all the detailed Google Shopping and platform-specific fields.
Converts messy source data into perfectly structured, multi-row CSVs or direct API payloads for various platforms.
Need a fresh take? Instantly rewrite product descriptions or generate new marketing copy from the data you've already collected.
The AI does the heavy lifting, but you're the final boss. Tweak titles, refine descriptions, manage images, and perfect every detail in our comprehensive editor before you publish.
While other tools simply scrape and translate, Katalyst uses advanced techniques that get smarter with every extraction.
Our system analyzes past successful extractions to improve future content. When processing electronics, it learns from other successful electronics listings.
The more you use it, the better it gets for your categories.
Every extraction gets a completeness score (0-1.0) based on data quality. You know exactly what needs manual review vs what's ready to publish.
מוצר טכנולוגי מתקדם זה כולל פיצ'רים רבים ויכולות מרשימות המיועדות לשיפור חוויית המשתמש שלך
Stiff, robotic, sounds like Google Translate
מכשיר חכם עם כל הפיצ'רים שאתה צריך - קל לתפעול ומושלם לשימוש יומיומי
Natural, conversational, sounds like an Israeli wrote it
You could. Here's what that looks like vs Katalyst:
What You Need | ChatGPT | Katalyst |
---|---|---|
Extract from complex PDFs | Struggles | Advanced parsing |
Find hidden product data | Only visible text | API interception |
Process 100+ products | One at a time | Parallel bulk |
Hebrew optimization | Generic | Israeli-trained |
Get better over time | Static | RAG learning |
Export-ready format | Manual | Perfect CSV |
For 5-10 products? Use ChatGPT.
For 100+ products? Katalyst saves days of work.
Launch SEO-ready Hebrew product pages today. Get your first product live in minutes.