We extract location coordinates, private office pricing, dedicated desk availability, and amenity lists from Venture X. Delivered as clean JSON, CSV, or Parquet to S3 or BigQuery.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Locations objects from venturex.com. All fields typed and schema-versioned.
"location_id": "VX-TX-042", "name": "Venture X Dallas - Braniff Centre", "city": "Dallas", "state": "TX", "zip_code": "75235", "latitude": 32.8361, "longitude": -96.8483
| # | location_id | name | address | city | state | zip_code |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Workspace Pricing objects from venturex.com. All fields typed and schema-versioned.
"location_id": "VX-TX-042", "workspace_type": "Private Office", "price_monthly": 650.0, "currency": "USD", "capacity_min": 1, "availability_status": "Available", "term_length": "Month-to-Month"
| # | location_id | workspace_type | price_monthly | currency | capacity_min | capacity_max |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Meeting Rooms objects from venturex.com. All fields typed and schema-versioned.
"location_id": "VX-TX-042", "room_name": "Boardroom A", "hourly_rate": 75.0, "capacity": 12, "av_equipment": true, "whiteboard_included": true
| # | location_id | room_name | hourly_rate | half_day_rate | full_day_rate | capacity |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Amenities objects from venturex.com. All fields typed and schema-versioned.
"location_id": "VX-TX-042", "amenity_category": "Facilities", "amenity_name": "High-Speed Internet", "is_premium": false, "available_24_7": true, "restrictions": "None"
| # | location_id | amenity_category | amenity_name | is_premium | description | icon_url |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Franchise Info objects from venturex.com. All fields typed and schema-versioned.
"location_id": "VX-TX-042", "franchisee_name": "Braniff Operations LLC", "square_footage": 22000, "building_class": "A", "transit_score": 54, "walk_score": 72
| # | location_id | franchisee_name | opening_date | square_footage | building_class | parking_capacity |
|---|---|---|---|---|---|---|
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Our Venture X scraper handles map-based rendering, dynamic pricing widgets, and location-specific DOM structures to deliver standardised commercial real estate data.
Extract every active and coming-soon Venture X location with precise geocoordinates and contact details.
Scrape private office, dedicated desk, and virtual office rates that load asynchronously on location pages.
Extract hourly rates, capacity limits, and AV equipment lists for every bookable meeting space.
Standardise unstructured amenity lists across franchisee pages into a clean, queryable format.
Execute JavaScript to trigger map-based location reveals and capture hidden JSON payloads.
Track new location announcements and ownership details across the global network.
Download high-resolution floor plans, gallery images, and virtual tour links.
Split raw address strings into structured street, city, state, and postal code fields.
Run weekly or monthly pipelines to detect pricing changes and new location openings.
Brief in. Clean data out.
Provide target regions or request a full global scrape. We map the required data points.
We configure Scrapy and Playwright to navigate the map interface and location templates.
Schema validation, null-rate checks, and coordinate verification before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket or Snowflake stage on agreed cadence.
Commercial real estate sites use dynamic map loads and fragmented templates. Here is how we extract clean data.
Venture X uses map widgets to display locations. We run headless browsers to execute the underlying JavaScript and intercept the API responses containing full coordinate data.
Individual locations often use slightly different page layouts. Our selector strategy uses fallback chains to ensure data extraction remains stable across the entire network.
Pricing for specific desk tiers often requires user interaction to load. We script these interactions to capture the final pricing state.
Amenities and workspace descriptions vary by location. We apply post-processing to map these variations to a normalised schema.
For real estate aggregators, we maintain a hash index of pricing and availability, emitting only the changes to reduce downstream processing.
Coworking operators track Venture X pricing tiers to optimise their own desk and office rates.
Investors analyse location density, square footage, and expansion patterns to evaluate market saturation.
Flexible workspace marketplaces ingest location and amenity data to populate their own booking engines.
B2B service providers extract contact details and franchisee information for targeted outreach.
City planners use coworking density metrics to model remote work trends and transit needs.
Retailers use premium coworking locations as a proxy for high-income professional foot traffic.
"Venture X represents a premium segment of the flexible workspace market, but extracting accurate pricing requires executing JavaScript across hundreds of location pages."
Most teams underestimate the complexity of scraping franchise-based sites. Location pages often use divergent templates, and pricing data loads asynchronously via map widgets. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our venturex.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 while Playwright executes the JavaScript required to render map interfaces and pricing widgets.
We route requests through ISP-grade residential proxies to prevent rate limiting and IP bans from real estate firewall protections.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, ensuring your location data is refreshed exactly when needed.
Data delivered to where your team already works — no new tooling required.
About venturex.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available location and pricing data is generally permissible. We do not extract personal member data or bypass authentication walls.
We use Playwright to execute the page JavaScript and intercept the underlying API calls that populate the map, extracting the raw JSON coordinates and location metadata.
Yes. We capture rates for private offices, dedicated desks, shared desks, and virtual offices, including capacity limits and term lengths where published.
For coworking directories, we typically run weekly or monthly pipelines, but we can configure daily runs if you need strict price monitoring.
Yes. We can extract high-resolution gallery images and PDF floor plans, delivering the raw files to your S3 bucket alongside the structured metadata.
Our selector strategy uses multiple fallback chains. If a specific location page deviates from the standard template, our pipeline flags the anomaly for manual review and selector updates.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off location dump or a continuous price-monitoring feed across all franchisee sites, we scope, build, and operate the pipeline.
