We extract complex furniture configurations, material matrices, dimensional specs, and regional pricing from Calligaris. 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 Product Listings objects from calligaris.com. All fields typed and schema-versioned.
"sku": "CS4128-FD_120", "name": "Orbital", "category": "Tables", "designer": "Pininfarina", "base_price": 4850.0, "currency": "EUR", "url": "https://www.calligaris.com/ea_en/shop/orbital-cs-4128-fd-120.html"
| # | sku | name | category | collection | designer | base_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Materials & Finishes objects from calligaris.com. All fields typed and schema-versioned.
"parent_sku": "CS4128-FD_120", "variant_sku": "CS4128-FD_120_P15_P5C", "frame_material": "Metal", "frame_finish": "Matte Black", "top_material": "Ceramic", "top_finish": "Salt White", "price_modifier": 350.0
| # | parent_sku | variant_sku | frame_material | frame_finish | top_material | top_finish |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Technical Specs objects from calligaris.com. All fields typed and schema-versioned.
"sku": "CS4128-FD_120", "width_cm": 165.0, "depth_cm": 105.0, "height_cm": 75.0, "weight_kg": 142.5, "assembly_required": true, "technical_pdf_url": "https://www.calligaris.com/media/pdf/CS4128.pdf"
| # | sku | width_cm | depth_cm | height_cm | seat_height_cm | weight_kg |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Assets & Media objects from calligaris.com. All fields typed and schema-versioned.
"sku": "CS4128-FD_120", "primary_image_url": "https://www.calligaris.com/media/catalog/product/o/r/orbital_1.jpg", "gallery_image_urls": "['https://www.calligaris.com/media/catalog/product/o/r/orbital_2.jpg']", "model_3d_url": "https://www.calligaris.com/media/3d/CS4128.gltf", "ar_asset_url": "https://www.calligaris.com/media/ar/CS4128.usdz", "video_url": "https://www.youtube.com/watch?v=example"
| # | sku | primary_image_url | gallery_image_urls | model_3d_url | ar_asset_url | video_url |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Store Locator objects from calligaris.com. All fields typed and schema-versioned.
"store_id": "ST-0042", "name": "Calligaris Store Milano", "type": "Flagship Store", "address": "Via Tivoli, 24", "city": "Milano", "country": "Italy", "latitude": 45.4731, "longitude": 9.1843
| # | store_id | name | type | address | city | country |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Calligaris scraper handles the complex configuration matrices of premium furniture, extracting every material combination, dimension, and regional price point with precision.
Extract categories, collections, and individual SKUs across seating, tables, beds, and storage units.
Iterate through complex client-side configurators to capture every valid combination of frame, fabric, and finish.
Parse unstructured dimension strings into clean numerical fields for width, depth, height, and weight.
Extract high-resolution gallery images, 3D model links (GLTF/OBJ), and AR asset URLs tied to specific variants.
Capture pricing across different regional domains (EU, US, UK) to monitor global price parity.
Map the entire retail footprint including flagship stores, official dealers, and their geographic coordinates.
Extract designer names and studio attributions for specific collections and flagship pieces.
Locate and download technical PDF specifications, assembly instructions, and care guides.
Run one-off bulk exports or configure continuous pipelines at weekly cadences with change-detection diffing.
Brief in. Clean data out.
Provide target categories, regions, or specific collections. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and configurator interaction logic for calligaris.com.
Schema validation, null-rate checks, and configuration matrix completeness verification before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Calligaris relies on heavy client-side rendering for product configurations. Here is how we extract complete matrices without missing variants.
Furniture configurators load base models and apply material logic client-side. We use Playwright to execute these state changes, ensuring we capture the exact price and asset link for every valid material combination.
Instead of merely scraping the DOM, our crawlers intercept and parse the underlying JSON state objects injected by modern frontend frameworks, capturing complete variant matrices in a single request.
We map specific swatch selections to their corresponding high-resolution gallery images and 3D model files, maintaining the relationship between the visual asset and the variant SKU.
We utilise residential EU proxies to bypass geo-blocking and basic WAF protections, ensuring consistent access to regional pricing and catalogue variations.
Furniture data is inherently nested. We flatten complex material combinations and dimensional data into strict, tabular schemas suitable for immediate insertion into relational warehouses.
Premium furniture retailers monitor Calligaris pricing across regions to inform their own pricing and discount strategies.
B2B design platforms aggregate 3D models, dimensions, and material specs to populate their digital planning tools.
Analysts track material combinations, finish availability, and collection lifecycles to map premium furniture trends.
Commercial real estate firms and competing brands map flagship stores and dealer networks to identify expansion opportunities.
Spatial computing and AR/VR developers extract architectural models and textures for use in virtual staging environments.
Design agencies analyse the prevalence of specific materials (e.g., ceramic vs. glass tops) across new collections.
"Calligaris presents a complex matrix of finishes and materials. Extracting the base product is easy; mapping the full configuration space requires a purpose-built pipeline."
Premium furniture sites use dynamic configurators that generate thousands of SKU permutations client-side. DataFlirt executes these state changes using headless browsers, capturing the exact price, dimension, and 3D asset link for every valid material combination, delivering structured catalogues ready for analysis.
Everything supported by our calligaris.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 handles JavaScript rendering and complex configurator interaction flows.
We maintain pools of residential proxies across EU and US regions to capture accurate localised pricing and bypass geographic routing restrictions.
Pipelines run on containerised infrastructure. Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About calligaris.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available catalogue and pricing information is generally permissible under applicable law. DataFlirt targets only public, non-authenticated product data. We do not extract personal data or circumvent authentication walls. Clients should consult legal counsel for specific use cases.
We use Playwright to simulate user interactions within the configurator, cycling through available materials, frame finishes, and fabric options to capture the complete matrix of valid SKUs and their associated price modifiers.
Yes. We extract the direct URLs to GLTF, OBJ, and USDZ files hosted on the platform, allowing interior design platforms to ingest these assets directly.
Yes. We route requests through region-specific residential proxies to capture accurate pricing in EUR, USD, GBP, or other supported currencies based on your requirements.
For furniture catalogues, we typically recommend weekly or bi-weekly runs. Full catalogue refreshes complete within a few hours. Change-detection diffing ensures you only process updated records.
Yes. We provide a sample run of up to 100 products, including their full variant configurations, so you can validate schema fit and data quality before signing a contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue dump or continuous price monitoring across regions — we scope, build, and operate the pipeline. Tell us what you need.
