We extract project portfolios, product specifications, material lists, firm intelligence, and high-res imagery from Archello. 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 Projects objects from archello.com. All fields typed and schema-versioned.
"project_id": "PRJ-992184", "title": "Oslo National Museum", "architect_firm": "Kleihues + Schuwerk", "location": "Oslo", "completion_year": 2022, "category": "Cultural", "area_sqm": 54600, "products_used": 34
| # | project_id | title | architect_firm | location | country | completion_year |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Products objects from archello.com. All fields typed and schema-versioned.
"product_id": "PRD-44192", "name": "Acoustic Wood Panels", "manufacturer": "Gustafs", "category": "Finishes", "sub_category": "Wall Cladding", "materials": "['Oak', 'MDF']", "projects_featured_in": 12, "specifications": "Fire Class A2-s1,d0"
| # | product_id | name | manufacturer | category | sub_category | description |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Firms objects from archello.com. All fields typed and schema-versioned.
"firm_id": "FRM-1029", "name": "Snøhetta", "type": "Architecture & Landscape", "location": "Oslo", "country": "Norway", "projects_count": 142, "specialties": "['Cultural', 'Commercial', 'Public Space']", "website": "snohetta.com"
| # | firm_id | name | type | location | country | website |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Complete list of extractable fields for Manufacturers objects from archello.com. All fields typed and schema-versioned.
"manufacturer_id": "MFG-8831", "name": "Vitra", "headquarters": "Birsfelden", "country": "Switzerland", "product_count": 412, "categories": "['Furniture', 'Lighting', 'Accessories']", "website": "vitra.com", "distributors": 84
| # | manufacturer_id | name | headquarters | country | product_count | categories |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Complete list of extractable fields for Materials & Specs objects from archello.com. All fields typed and schema-versioned.
"spec_id": "SPC-9912", "project_id": "PRJ-992184", "product_id": "PRD-44192", "application_type": "Interior Wall", "material_type": "Timber", "colour": "Natural Oak", "finish": "Matte Lacquer", "sustainability_rating": "FSC Certified"
| # | spec_id | project_id | product_id | application_type | material_type | colour |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Our Archello scraper navigates complex relational data, linking architectural projects to the exact products, manufacturers, and materials specified, while handling heavy media payloads and infinite scroll.
Extract full project metadata including architect credits, location data, completion year, area metrics, and detailed descriptions.
Capture product dimensions, material compositions, available finishes, certifications, and BIM metadata.
Extract the relational links showing exactly which products and materials were specified in specific architectural projects.
Gather profiles on architecture and interior design firms, including project counts, specialisations, and location data.
Scrape full product lines from global brands, categorised by application, material, and room type.
Extract direct URLs for high-resolution project photography, floor plans, and product imagery.
Capture specific material applications, colourways, and finish details documented within project specifications.
Identify patterns in which architecture firms frequently specify products from specific manufacturers.
Track new project uploads, product launches, and firm portfolio updates on a daily or weekly schedule.
Brief in. Clean data out.
Provide target categories, firm locations, or manufacturer names. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and session management for archello.com.
Schema validation, null-rate checks, and relational mapping verification before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Scraping rich media platforms requires handling heavy JS, infinite scroll, and complex relational mapping. Here is how we maintain pipeline stability.
Archello relies heavily on client-side rendering for project galleries and product specifications. We run full Playwright browser sessions to ensure all dynamic components hydrate before extraction.
Project lists and manufacturer catalogues use infinite scroll. Our crawlers simulate human scrolling behaviour to trigger lazy-loaded XHR requests, ensuring complete capture of long lists without triggering bot protections.
The value in Archello data is the relationship between entities. Our pipeline maintains strict foreign key relationships, ensuring you can query exactly which firm used which product in which project.
Downloading thousands of high-res images directly slows pipelines and spikes bandwidth costs. We extract clean, direct CDN URLs for all media assets, allowing you to download them asynchronously on your end.
For tracking firm portfolios, we maintain a hash index of last-seen projects. Subsequent runs only push new projects or updated specifications, reducing downstream processing load.
Building material manufacturers track where their products, and their competitors' products, are specified globally.
Sales teams identify architecture firms designing specific project types (e.g., healthcare, commercial) to target outreach.
Design analysts identify trending materials, finishes, and colours across recent high-profile architectural projects.
Track new product launches, specification updates, and categorisation changes by rival manufacturers.
ML teams use structured project metadata and high-quality imagery to train generative design and classification models.
Software vendors target architecture firms based on project volume, firm size, and specialisation.
"Archello maps the built environment by connecting projects to the exact products used — but extracting that relational graph requires purpose-built infrastructure."
Most teams fail at extracting architecture platforms because they cannot handle the heavy JavaScript payloads, infinite scroll pagination, and complex many-to-many relationships between projects, architects, and manufacturers. DataFlirt manages this complexity entirely. Your team receives clean, relational data ready for analysis.
Everything supported by our archello.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, infinite scroll, and dynamic content hydration.
We maintain pools of residential ISP proxies to handle rate limits and IP reputation checks, rotating per request to ensure uninterrupted extraction.
Pipelines run on AWS Lambda and ECS. 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 archello.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information is generally permissible under applicable law. DataFlirt targets only public, non-authenticated project, product, and firm data. We do not circumvent authentication walls or extract private user data. Clients should review terms of service and consult legal counsel for specific use cases.
Our pipelines are designed to capture foreign keys. When we scrape a project, we extract the IDs of all specified products. When we scrape those products, they maintain that relational link, allowing you to reconstruct the graph in your own database.
To optimise pipeline speed and reduce your storage costs, we extract the direct, high-resolution CDN URLs for all images and floor plans. You can then download these assets asynchronously using your own infrastructure.
We use residential ISP proxies and configure our crawlers to mimic human browsing behaviour, including randomised delays between scroll events and XHR requests, ensuring we capture the entire portfolio without triggering blocks.
For tracking new projects or product launches, we typically run daily or weekly delta pipelines. Full catalogue refreshes are usually scheduled monthly depending on your requirements.
Our smallest packages start at defined categories or specific manufacturer lists. For full-site extraction, we price based on volume and delivery frequency. Contact us with your target scope.
Yes. We provide a sample run of up to 100 projects and their associated products as part of the pre-engagement scoping process, allowing you to validate the schema and relational mapping.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off extraction of specific firm portfolios or a continuous feed of new project specifications — we scope, build, and operate the pipeline. Tell us what you need.
