We extract office listings, lease rates, building classifications, floor plans, and broker details from officespace.com. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your schedule.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Property Listings objects from officespace.com. All fields typed and schema-versioned.
"property_id": "OS-94812", "title": "Downtown Tech Tower", "address": "400 Broad St", "city": "Seattle", "state": "WA", "zip_code": "98109", "property_type": "Office", "building_class": "A", "year_built": 2018, "total_sqft": 450000
| # | property_id | title | address | city | state | zip_code |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Lease Availability objects from officespace.com. All fields typed and schema-versioned.
"listing_id": "L-39201", "suite_number": "Suite 1200", "floor": 12, "available_sqft": 15000, "lease_rate_annual": 45.0, "lease_type": "NNN", "availability_date": "2026-01-01", "space_use": "Office"
| # | listing_id | property_id | suite_number | floor | available_sqft | min_divisible_sqft |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Broker Information objects from officespace.com. All fields typed and schema-versioned.
"broker_id": "BRK-7732", "name": "Sarah Jenkins", "firm_name": "CBRE", "phone_number": "+1-206-555-0199", "active_listings_count": 24, "markets_served": "['Seattle', 'Bellevue']", "specialties": "['Tenant Representation', 'Office Leasing']"
| # | broker_id | name | firm_name | phone_number | email_address | license_number |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Building Amenities objects from officespace.com. All fields typed and schema-versioned.
"property_id": "OS-94812", "has_fitness_center": true, "transit_score": 98, "walk_score": 95, "leed_certification": "Gold", "security_type": "24/7 Attended Lobby", "bike_storage": true
| # | property_id | has_fitness_center | has_cafe | transit_score | walk_score | leed_certification |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Submarket Data objects from officespace.com. All fields typed and schema-versioned.
"market_name": "Seattle", "submarket_name": "South Lake Union", "total_inventory_sqft": 12500000, "vacancy_rate_pct": 8.4, "average_asking_rate": 52.5, "net_absorption_sqft": 350000, "under_construction_sqft": 1200000
| # | market_id | market_name | submarket_name | total_inventory_sqft | vacancy_rate_pct | average_asking_rate |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our officespace.com scraper targets commercial property listings, standardising lease variables, building classifications, and broker details across the entire catalogue.
Capture building class, year built, total square footage, parking ratios, and exact geocoordinates for every commercial asset.
Extract and normalise lease rates, distinguishing between NNN, Full Service Gross, and Modified Gross lease types.
Track minimum divisible and maximum contiguous square footage metrics for individual suites and floors.
Extract listing agent details, firm affiliations, contact numbers, and active portfolio counts.
Bypass standard pagination limits by executing spatial queries across map boundaries to guarantee full market coverage.
Identify flexible workspace listings, desk rates, and operator details separate from traditional direct leases.
Capture LEED certifications, transit scores, and on-site amenities to enrich property valuation models.
Monitor markets for new listings, rate adjustments, and spaces removed from the market to calculate absorption.
Extract URLs for property brochures, floor plan PDFs, and image galleries for downstream processing.
Brief in. Clean data out.
Provide target MSAs, property types, or specific brokerage filters. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and map-boundary traversal logic for officespace.com.
Schema validation, lease rate normalisation checks, and spatial deduplication before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Scraping commercial listings requires navigating spatial search limits and unstructured lease formats. Here is how we build resilient pipelines.
Property portals limit search results in dense urban cores. Our crawlers divide target markets into granular bounding boxes, traversing the map programmatically to ensure zero missed listings in high-density areas.
Brokers input rates in monthly, annual, or per-square-foot formats. Our pipeline parses the raw text and standardises these values into a uniform annual per-square-foot metric for direct comparison.
Broker contact information is often gated behind client-side JavaScript interactions. We run Playwright to simulate user clicks, revealing phone numbers and email addresses hidden from static HTTP requests.
The same physical building may have multiple concurrent listings from different brokers. We use address normalisation and coordinate matching to link suites to a single parent property entity.
Real estate aggregators monitor traffic patterns to block automated collection. We route requests through US residential IPs with randomised delays and realistic browser fingerprints to maintain uninterrupted access.
Private equity and REIT analysts track asking rates and vacancy trends to evaluate acquisition targets and underwrite properties.
Brokerage teams aggregate market-wide availability to identify off-market opportunities and negotiate favourable lease terms.
Real estate software platforms enrich their internal databases with active listings, building specs, and broker directories.
Economists and urban planners monitor net absorption and inventory growth to assess the economic health of commercial districts.
Commercial service providers target new corporate relocations and office build-outs by tracking newly signed leases and available suites.
Appraisers correlate building amenities, LEED certifications, and transit scores with lease premiums to refine automated valuation models.
"Officespace.com maps the commercial real estate landscape, but standardising lease rates and building specs across thousands of listings requires a dedicated extraction pipeline."
Most teams underestimate the complexity of commercial real estate data. Standardising NNN versus Full Service leases, parsing variable floor plan formats, and handling map-based pagination requires dedicated infrastructure. DataFlirt absorbs that complexity so your analysts can focus on market yields.
Everything supported by our officespace.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 manages request queues based on geographic grids. Playwright handles interactive map elements and contact reveals. Combined via custom middleware for real estate targets.
We route traffic through US-based residential ISP proxies. Rotation occurs per coordinate grid to prevent rate limiting and ensure complete market coverage without IP bans.
Extraction runs on AWS Lambda and ECS. Airflow schedules daily or weekly market sweeps. Post-processing normalises lease rates before loading into managed Postgres.
Data delivered to where your team already works — no new tooling required.
About officespace.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly accessible property listings and broker directories is generally permissible. DataFlirt targets only public, non-authenticated data. We do not extract proprietary tenant databases or bypass authenticated broker portals. Clients should review target platform terms and consult legal counsel for specific applications.
Commercial platforms often cap search results at 500 properties. We divide target Metropolitan Statistical Areas into granular latitude and longitude bounding boxes, querying each micro-region separately to guarantee 100% market coverage.
Yes. Brokers list rates differently depending on the market. Our pipeline parses the raw text and standardises values into a uniform annual per-square-foot metric, clearly tagging the lease type (NNN, Full Service, etc.).
We extract the direct URLs to PDF brochures, floor plans, and image galleries. You receive the structured links, which your systems can use to download the media files directly.
Most commercial real estate clients opt for weekly or bi-weekly market sweeps, as commercial inventory moves slower than residential. However, we can configure daily pipelines for specific high-velocity submarkets.
Our smallest packages start at tracking specific submarkets or property classes. For national coverage across multiple MSAs, we price based on the geographic scope and update frequency. Contact us with your target markets for a quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off extraction of a specific submarket or continuous monitoring of national office inventory, we build and operate the pipeline. Tell us what you need.
