We extract complex jewellery configurations, dynamic metal pricing, gemstone variants, and design specs from Gemvara. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Base Designs objects from gemvara.com. All fields typed and schema-versioned.
"sku": "GV-R-1042", "title": "Brilliant Solitaire Ring", "category": "Rings", "style": "Solitaire", "base_price": 850.0, "metal_options": "['14K White Gold', '18K Yellow Gold', 'Platinum']", "stone_options": "['Diamond', 'Sapphire', 'Ruby', 'Emerald']", "default_image_url": "https://images.gemvara.com/GV-R-1042-default.jpg"
| # | sku | title | category | style | collection | base_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Configured Pricing objects from gemvara.com. All fields typed and schema-versioned.
"config_id": "GV-R-1042-18KY-DIA-100", "base_sku": "GV-R-1042", "selected_metal": "18K Yellow Gold", "selected_center_stone": "Diamond", "ring_size": "6.5", "final_price": 2450.0, "currency": "USD", "price_timestamp": "2026-05-12T10:15:00Z"
| # | config_id | base_sku | selected_metal | selected_center_stone | selected_accent_stones | ring_size |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Gemstone Data objects from gemvara.com. All fields typed and schema-versioned.
"stone_name": "Round Brilliant Diamond", "stone_type": "Natural Diamond", "cut": "Excellent", "carat_weight": 1.0, "color_grade": "G", "clarity": "VS2", "price_premium": 4200.0
| # | stone_name | stone_type | cut | carat_weight | dimensions | color_grade |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Metal Specs objects from gemvara.com. All fields typed and schema-versioned.
"metal_name": "18K Rose Gold", "purity": "75% Gold", "color": "Rose", "alloy_composition": "Gold, Copper, Silver", "base_cost": 85.5, "weight_grams": 4.2, "availability": "In Stock"
| # | metal_name | purity | color | alloy_composition | base_cost | weight_grams |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Product Reviews objects from gemvara.com. All fields typed and schema-versioned.
"review_id": "REV-99482", "product_sku": "GV-R-1042", "star_rating": 5, "review_title": "Perfect engagement ring", "verified_buyer": true, "date_posted": "2025-11-04", "helpful_votes": 12
| # | review_id | product_sku | reviewer_name | star_rating | review_title | review_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Gemvara's value lies in its dynamic customisation engine. Our scraper executes JavaScript to iterate through metal types, gemstone cuts, and sizing options, extracting the full pricing matrix for every design.
Programmatically iterate through metal and stone combinations to capture the complete configuration matrix for any base design.
Extract precise pricing updates generated by Gemvara's frontend logic based on material and size selections.
Capture image assets and rendering URLs for every specific metal and gemstone variation.
Extract standard metadata for rings, necklaces, earrings, and bracelets including style tags and collection names.
Structure cut, clarity, carat weight, and colour grades for all available centre and accent stones.
Track pricing tiers and specifications for 14k, 18k, Platinum, Palladium, and Sterling Silver options.
Paginate through customer feedback, capturing star ratings, verified purchase status, and full text reviews.
Navigate the site hierarchy to map products to their respective categories, sub-categories, and thematic collections.
Run daily or weekly pipelines to detect retail price fluctuations driven by underlying spot metal markets.
Brief in. Clean data out.
Provide specific collections, categories, or base SKUs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and DOM interaction logic for gemvara.com.
Schema validation, null-rate checks, price-outlier detection, and sample configurations before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting data from a highly dynamic, JavaScript-driven customisation engine requires deep interaction logic. Here is how we build resilience.
Gemvara's pricing and imagery only generate when a user selects specific swatches. We run full browser sessions to programmatically click through metal and stone combinations, waiting for AJAX requests to resolve before capturing the final price.
A single ring can have thousands of variations. We use bounded iteration logic to extract a representative matrix of prices without triggering infinite loops or redundant network requests.
Rapidly clicking through a configurator triggers rate limits. We use US residential proxies and introduce randomised delays between swatch selections to mimic legitimate user behaviour.
Frontend frameworks frequently regenerate class names. We map selectors to stable data attributes and JSON payloads in the page source to ensure the pipeline survives UI updates.
We maintain a state cache of the configuration matrix. Subsequent runs only export records where the final retail price has shifted, reducing your ingestion costs.
Direct-to-consumer jewellery brands track Gemvara's retail pricing across specific metal and stone combinations to position their own catalogues.
Pricing analysts correlate Gemvara's retail price adjustments with raw spot gold and silver markets to reverse-engineer markup strategies.
Merchandising teams analyse the expansion or contraction of specific gemstone offerings to identify consumer trends.
Machine learning teams use structured design specifications and paired high-resolution imagery to train generative AI models for jewellery design.
Industry analysts track review velocity and collection sizes to estimate category performance and brand momentum.
Supply chain teams isolate the price premium charged for specific diamond cuts or clarity grades versus base metal costs.
"Gemvara's configurator generates millions of possible jewellery permutations. Extracting this matrix requires deep interaction, not static HTML parsing."
Standard HTTP requests fail against Gemvara's dynamic interface. We deploy headless browsers to programmatically select metals, stones, and sizes, capturing the exact price and specification output for every permutation. DataFlirt manages the interaction logic so you receive a flat, structured catalogue ready for analysis.
Everything supported by our gemvara.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration and deduplication. Playwright drives the browser sessions required to interact with the Gemvara configurator.
We maintain pools of US residential ISP proxies to handle the high volume of requests generated by iterating through product permutations.
Pipelines run on scalable container infrastructure. Airflow handles scheduling and dependency management, pushing clean data to your warehouse.
Data delivered to where your team already works — no new tooling required.
About gemvara.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available product, pricing, and review data is generally permissible. DataFlirt targets only public pages and does not extract personal data or bypass authentication walls. Clients should review Gemvara's terms of service and consult legal counsel for specific use cases.
We work with you to define the required scope. Instead of scraping every mathematically possible combination, we target the specific metals, centre stones, and sizes relevant to your analysis, configuring the crawler to iterate only through those matrices.
Yes. As the Playwright session selects different swatches, the frontend updates the image asset. We capture the URL of the rendered image corresponding to that exact configuration.
Pipelines can be configured to run daily or weekly. Given the computation required to iterate through configurators, full catalogue refreshes typically run over a 12 to 24 hour window.
Yes. Our change detection system flags SKUs that return 404s or are removed from the category index, marking them as inactive in your dataset rather than deleting the historical record.
Yes. We provide a sample run of up to 50 base designs and their associated configurations to validate schema fit and data completeness before contract signature.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a complete catalogue extraction or continuous tracking of specific metal and stone configurations, we build and operate the infrastructure. Tell us what you need.
