We extract project portfolios, material specifications, firm profiles, and professional networks from Archilovers. 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 archilovers.com. All fields typed and schema-versioned.
"project_id": "PRJ-98214", "title": "Milan Central Pavilion", "location": "Milan, Italy", "year_completed": 2024, "status": "Completed", "firm_name": "Studio Rossi Architecture", "style_category": "Contemporary", "materials_used": "['Concrete', 'Glass', 'Steel']"
| # | project_id | title | location | year_completed | status | firm_id |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Firms objects from archilovers.com. All fields typed and schema-versioned.
"firm_id": "FRM-4412", "name": "Studio Rossi Architecture", "type": "Architecture Studio", "location": "Milan, Italy", "founded_year": 2008, "project_count": 47, "follower_count": 12403, "specialisations": "['Commercial', 'Public Spaces']"
| # | firm_id | name | type | location | website_url | founded_year |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Professionals objects from archilovers.com. All fields typed and schema-versioned.
"user_id": "USR-88321", "name": "Elena Bianchi", "role": "Lead Architect", "location": "Rome, Italy", "firm_id": "FRM-4412", "project_count": 12, "follower_count": 3412, "skills": "['Urban Planning', 'Sustainable Design']"
| # | user_id | name | role | location | bio | firm_id |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Products objects from archilovers.com. All fields typed and schema-versioned.
"product_id": "PROD-7721", "name": "Lumina Pendant Lamp", "brand": "Luceplan", "category": "Lighting > Pendants", "materials": "['Aluminium', 'Polycarbonate']", "project_mentions": 142, "designer": "Paolo Rizzatto"
| # | product_id | name | brand | designer | category | materials |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Brands objects from archilovers.com. All fields typed and schema-versioned.
"brand_id": "BRD-991", "name": "Luceplan", "country": "Italy", "product_count": 312, "project_count": 4192, "follower_count": 28411, "categories": "['Lighting', 'Acoustic Solutions']"
| # | brand_id | name | country | website | description | product_count |
|---|---|---|---|---|---|---|
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Our Archilovers scraper maps the complex relationships between projects, the firms that designed them, and the materials they used. We handle infinite scrolling, image CDNs, and multi-language content automatically.
Extract project metadata including year, location, status, tags, and full descriptive text across multiple languages.
Capture firm details, specialisations, employee counts, and aggregate portfolio statistics.
Extract product catalogues, designer attribution, material composition, and dimensional data.
Maintain the exact links between a project, the firm that built it, the professionals involved, and the products installed.
Scrape high-resolution image URLs, alt text, and gallery sequencing without downloading the heavy binary files.
Extract and categorise architectural styles, material tags, and building typologies into structured arrays.
Parse unstructured location strings into standard city, region, and country fields for geospatial analysis.
Map follower graphs, professional associations, and skill endorsements across user profiles.
Run recurring pipelines that only emit new projects or updated portfolios, reducing your ingestion overhead.
Brief in. Clean data out.
Provide target categories, specific firm URLs, or regional filters. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for archilovers.com.
Schema validation, null-rate checks, and relational integrity testing before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Archilovers relies on heavy JavaScript hydration and complex pagination. Here is how we maintain pipeline stability.
Archilovers project galleries and firm portfolios load dynamically via JavaScript. We use Playwright to simulate user scroll behaviour, ensuring all XHR requests fire and all items are captured before extraction begins.
A single project page references firms, products, and professionals. Our pipeline extracts these entities and assigns deterministic IDs, allowing you to reconstruct the exact graph in your relational database.
To avoid IP bans during deep crawls of large firm portfolios, we route traffic through EU-based residential proxies. This distributes the request load and mirrors normal professional browsing behaviour.
Archilovers serves content in multiple languages. We force the locale via headers and URL parameters to ensure your dataset maintains a consistent language for descriptions and categorisations.
We monitor DOM structure changes daily. If Archilovers updates their project page layout, our multi-layered selectors fall back to JSON-LD metadata, and our engineers are alerted to patch the primary selectors.
Material and furniture suppliers track new project announcements to identify active firms for targeted outreach.
Analysts track the adoption of specific materials (e.g., cross-laminated timber) or architectural styles across different regions.
Architecture firms monitor competitor portfolios, client networks, and project completion velocities.
Machine learning teams use structured project metadata and image URLs to train generative design models.
Recruiters extract professional profiles and project histories to source specialised architects and interior designers.
Furniture and lighting brands track how often their products are specified in high-profile projects.
"Archilovers maps the global architecture ecosystem, but connecting projects to the exact materials and firms requires a structured data pipeline."
Most teams underestimate the investment required: reliable Archilovers scraping requires residential proxies, infinite scroll handling, CAPTCHA bypass, and complex relational mapping between projects, products, and professionals. DataFlirt absorbs that complexity so your engineers can focus on the analysis.
Everything supported by our archilovers.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, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda (burst) and ECS (sustained). 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 archilovers.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, firm, and product data. We do not extract private messages or behind-login analytics. Clients should review platform terms and consult legal counsel for specific use cases.
Our schema assigns deterministic IDs to entities. When we scrape a project, we extract the firm URL/ID and product IDs associated with it. This allows you to load the flat files into a relational database and instantly join projects to their respective creators and materials.
We extract the high-resolution CDN URLs and their associated metadata (alt text, sequence order). We do not download the binary image files by default to save bandwidth and storage, but you can feed these URLs into your own ingestion scripts.
Yes. We can seed the crawler with specific location filters, tag URLs, or a predefined list of firm profiles to restrict the extraction scope to your target market.
We use Playwright to execute full browser sessions, simulating human scroll behaviour and waiting for network idle states to ensure all paginated items are loaded into the DOM before extraction.
Our smallest packages start at a defined list of firms or a specific regional category. For entire platform syncs, we price based on compute volume and delivery frequency. Contact us with your target scope.
Yes. We provide a sample run of up to 100 projects or firm profiles during the scoping phase. This allows your engineering team to validate the schema and relational mapping before signing a contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a targeted list of regional architecture firms or a continuous feed of new project materials, we build and operate the pipeline. Tell us what you need.
