We extract location coordinates, membership pricing, meeting room availability, and workspace amenities from Serendipity Labs. 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 Location Data objects from serendipitylabs.com. All fields typed and schema-versioned.
"location_id": "SL-NYC-01", "name": "New York - Financial District", "city": "New York", "state": "NY", "zip_code": "10005", "latitude": 40.7061, "longitude": -74.0092, "status": "Open"
| # | location_id | name | address | city | state | zip_code |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Membership Pricing objects from serendipitylabs.com. All fields typed and schema-versioned.
"location_id": "SL-NYC-01", "plan_type": "Coworking 10", "price_monthly": 299.0, "currency": "USD", "access_level": "Business Hours", "guest_passes": 2, "mail_handling": false
| # | location_id | plan_type | price_monthly | currency | setup_fee | access_level |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Private Offices objects from serendipitylabs.com. All fields typed and schema-versioned.
"office_id": "PO-NYC-01-402", "location_id": "SL-NYC-01", "capacity_min": 2, "capacity_max": 4, "price_monthly": 1850.0, "window_view": true, "availability_status": "Available Now", "furnished": true
| # | office_id | location_id | capacity_min | capacity_max | price_monthly | availability_status |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Meeting Rooms objects from serendipitylabs.com. All fields typed and schema-versioned.
"room_id": "MR-NYC-01-A", "location_id": "SL-NYC-01", "room_name": "Executive Boardroom", "capacity": 12, "price_hourly": 120.0, "price_full_day": 800.0, "av_equipment": true, "whiteboard": true
| # | room_id | location_id | room_name | capacity | price_hourly | price_half_day |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Amenities objects from serendipitylabs.com. All fields typed and schema-versioned.
"location_id": "SL-NYC-01", "has_parking": false, "has_cafe": true, "has_mother_room": true, "has_focus_rooms": true, "building_class": "Class A", "security_type": "24/7 Lobby Attendant"
| # | location_id | has_parking | has_cafe | has_mother_room | has_focus_rooms | has_event_space |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our scraper handles map locators, dynamic pricing widgets, and regional variations with JavaScript rendering and anti-bot circumvention built in.
Extract every active and upcoming location, including addresses, coordinates, and contact information.
Capture local pricing for coworking plans, dedicated desks, and day passes across different markets.
Track pricing and capacity constraints for private suites and team rooms based on real-time availability widgets.
Extract hourly and daily rates, seating capacities, and included AV equipment for bookable spaces.
Capture mail handling, business address, and phone answering service rates per location.
Extract facility features including cafes, parking availability, mother rooms, and transit proximity.
Compare identical membership tiers across different cities and states to map pricing strategies.
Capture staffed hours versus 24/7 access rules for different membership levels.
Run continuous pipelines to detect new location openings, price adjustments, and facility closures.
Brief in. Clean data out.
Provide target regions or request a full national extraction. We design the schema together.
We configure Playwright crawlers, proxy rotation, and session management to handle map locators.
Schema validation, null-rate checks, and price-outlier detection before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting accurate pricing from flexible workspace providers requires handling dynamic web applications. Here is how we stay resilient.
We use US-based residential ISP proxies with realistic browser fingerprints to prevent IP blocking during full site crawls.
Location directories rely on interactive maps and JavaScript hydration. We use full browser sessions to trigger location loads and extract hidden coordinates.
We use multiple fallback chains per field so minor layout updates to pricing tables do not break your data feed.
Private office pricing often requires selecting capacity tiers. Our crawlers iterate through form options to extract the full pricing matrix.
We maintain a hash index of last-seen values per field. Subsequent runs only push diffs, providing a clean changelog of price hikes.
Coworking operators track Serendipity Labs pricing across local markets to adjust their own desk and office rates.
Commercial real estate firms analyze location density and expansion patterns to identify emerging business districts.
Enterprise teams map flexible workspace availability against employee distribution to plan hybrid work strategies.
Workspace booking platforms ingest location and amenity data to maintain accurate marketplace listings.
Analysts track new location openings and closures to evaluate brand health and regional market share.
Developers assess standard building features and transit proximity requirements for Class-A flexible office spaces.
"Flexible workspace pricing is highly localized and constantly shifting. Extracting accurate rates requires parsing dynamic booking widgets across every single location."
Most teams underestimate the investment required: reliable Serendipity Labs scraping requires residential proxies, full JavaScript rendering for map locators, and daily selector maintenance. DataFlirt absorbs that complexity so your engineers can focus on the analysis.
Everything supported by our serendipitylabs.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 retry logic. Playwright handles JavaScript rendering and interaction flows for map locators.
We maintain pools of US residential ISP proxies. Rotation happens per-request to prevent bot mitigation blocks.
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 serendipitylabs.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available location and pricing data is generally permissible. DataFlirt targets only public, non-authenticated pages. We do not extract personal data or circumvent authentication walls.
We use Playwright to execute the JavaScript required to render map interfaces and intercept the XHR/fetch requests containing the raw coordinate and location metadata.
Yes. Every pipeline run produces timestamped snapshots. We maintain a time-series record for membership and office pricing.
Yes, we capture minimum and maximum seating capacities, along with included amenities and tiered pricing models (hourly, half-day, full-day).
Full site refreshes can be scheduled daily, weekly, or monthly depending on your requirements. The extraction completes within hours.
Yes, we extract pricing and inclusions for virtual office services, including mail handling and business address usage.
We price based on extraction frequency and complexity. Contact us with your specific data requirements for a scoped quote.
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 — we scope, build, and operate the pipeline. Tell us what you need.
