We extract collections, designer profiles, material matrices, store locations, and configuration assets from Molteni. 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 Products & Collections objects from molteni.com. All fields typed and schema-versioned.
"product_id": "MLT-SOF-092", "name": "Paul", "collection": "Molteni&C", "designer": "Vincent Van Duysen", "year": 2016, "category": "Sofas", "description": "Elegant seating system with generous proportions.", "url": "https://www.molteni.com/en/product/paul"
| # | product_id | name | collection | designer | year | category |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Finishes & Materials objects from molteni.com. All fields typed and schema-versioned.
"product_id": "MLT-SOF-092", "finish_category": "Upholstery", "material_name": "Leather", "colour_code": "L Extra", "colour_name": "Testa di Moro", "texture_image_url": "https://cdn.molteni.com/textures/l-extra-testa-di-moro.jpg", "availability_tier": "Premium", "care_instructions": "Professional leather cleaning only."
| # | product_id | finish_category | material_name | colour_code | colour_name | texture_image_url |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Designer Profiles objects from molteni.com. All fields typed and schema-versioned.
"designer_id": "DES-VVD-01", "full_name": "Vincent Van Duysen", "studio_name": "Vincent Van Duysen Architects", "biography": "Born in Lokeren, Belgium, in 1962.", "country": "Belgium", "associated_products": "['Paul', 'Ribbon', 'Gliss Master']", "profile_image_url": "https://cdn.molteni.com/designers/vvd.jpg"
| # | designer_id | full_name | studio_name | biography | country | website |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Technical Assets objects from molteni.com. All fields typed and schema-versioned.
"product_id": "MLT-SOF-092", "asset_type": "Technical Sheet", "file_name": "paul_tech_sheet_en.pdf", "file_url": "https://cdn.molteni.com/assets/paul_tech_sheet_en.pdf", "file_size_kb": 2450, "file_format": "PDF", "language": "en", "last_updated": "2025-01-14T00:00:00Z"
| # | product_id | asset_type | file_name | file_url | file_size_kb | file_format |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Store Locator objects from molteni.com. All fields typed and schema-versioned.
"store_id": "STR-MIL-01", "store_name": "Molteni&C Flagship Store Milano", "store_type": "Flagship", "address_line_1": "Corso Europa, 2", "city": "Milan", "country": "Italy", "latitude": 45.4642, "longitude": 9.19, "services_offered": "['Interior Design Service', 'Configurator Access']"
| # | store_id | store_name | store_type | address_line_1 | city | postal_code |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Molteni's catalogue relies heavily on dynamic WebGL configurators, high-resolution image matrices, and nested collection hierarchies. We parse the frontend to deliver structured JSON.
Map individual products to their overarching collections and capture designer attribution, launch year, and primary category.
Scrape every available configuration option, including fabric grades, leather types, wood veneers, and metal finishes with corresponding texture URLs.
Extract width, depth, height, and modular seating configurations directly from product pages and structural DOM elements.
Index URLs for 2D/3D CAD models, BIM objects, assembly instructions, and technical specification PDFs per product.
Compile biographical data, studio information, and complete product lists for every designer featured on the platform.
Extract the complete global store directory, including flagship boutiques, authorised dealers, geocoordinates, and contact details.
Capture URLs for lifestyle shots, isolated product photography, and detailed material close-ups at maximum resolution.
Track product availability and catalogue differences across European, North American, and Asian regional sites.
Identify newly added products, discontinued lines, and updated finish options with hash-based change detection.
Brief in. Clean data out.
Provide target collections, designer lists, or specific asset types. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, handle WebGL configurator state, and manage regional proxy routing.
Schema validation, null-rate checks, asset link verification, and sample matrix exports before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting data from luxury design sites requires handling heavy visual assets and dynamic configuration engines. Here is how we build it.
Molteni uses complex configurators for modular furniture. We use Playwright to execute JavaScript, iterate through configurator states, and intercept XHR responses to capture the full matrix of available finishes and dimensions.
Technical sheets and CAD files are often loaded dynamically or gated behind forms. Our crawlers simulate user interactions to expose secure download links and index them directly into your database.
Luxury furniture sites serve massive image payloads. We intercept image requests to extract base URLs and construct maximum-resolution links without downloading the payload during the crawl, saving bandwidth and time.
Product availability varies by region. We route requests through residential proxies in specific target countries (e.g., Italy, USA, Japan) to capture accurate regional catalogues and store locators.
For the Molteni catalogue, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs - reducing compute cost, storage bloat, and downstream processing load.
Platforms ingest Molteni product specs, dimensions, and CAD assets to build comprehensive search engines for interior architects.
Luxury furniture brands monitor Molteni's new collection launches, designer collaborations, and material introductions.
Design analysts track the frequency of specific finishes (e.g., travertine, smoked oak) across the catalogue to predict industry trends.
Market researchers plot Molteni's global store locator data to analyse retail expansion strategies in emerging luxury markets.
Architecture software providers index direct links to Molteni's 3D models to populate their internal rendering libraries.
ML teams train spatial arrangement models using precise dimensional data and modular configuration rules extracted from the catalogue.
"Molteni's digital catalogue contains the exact dimensional and material data required for architectural planning, but accessing it systematically requires a purpose-built extraction pipeline."
Extracting data from luxury furniture platforms involves navigating heavily JavaScript-dependent interfaces, WebGL configurators, and massive image payloads. DataFlirt handles the rendering, state management, and asset linking so your team can focus on integrating the data into your design software or analytics dashboard.
Everything supported by our molteni.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, configurator state iteration, and XHR interception.
We maintain pools of residential ISP proxies to route requests through specific countries, ensuring accurate capture of regional catalogue variations.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About molteni.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from molteni.com is generally permissible for non-copyright-infringing factual data (dimensions, materials, store locations). DataFlirt targets only public, non-authenticated data. Clients should review Molteni's ToS and consult legal counsel for specific commercial use cases.
We use Playwright to execute the JavaScript required to load the configurator. We then intercept the underlying API calls or iterate through the DOM state to capture the complete matrix of available finishes, modules, and dimensions.
We extract and index the direct download URLs for these assets. If required, we can configure a secondary pipeline to download the actual files to your S3 bucket, though most clients prefer URL indexing to manage storage costs.
For furniture catalogues, we typically run weekly or monthly full-site refreshes. A complete extraction of the Molteni catalogue and all finish matrices takes approximately 4-8 hours.
Yes. We can configure the pipeline to crawl the site from multiple geographic locations (e.g., Italy, USA, UK) to capture region-specific product availability and store listings.
Yes. We provide a sample run covering a specific collection or designer to validate schema fit, asset link reliability, 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 export for a design aggregator or continuous monitoring of new collections - we scope, build, and operate the pipeline. Tell us what you need.
