We extract company profiles, firmographics, industry classifications, and technology stack data from UpLead. 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 Company Profiles objects from uplead.com. All fields typed and schema-versioned.
"company_name": "Acme Corp", "domain": "acmecorp.com", "industry": "Enterprise Software", "revenue_estimate": "50M-100M", "employee_count": 450, "year_founded": 2012
| # | company_name | domain | industry | revenue_estimate | employee_count | year_founded |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Technology Stack objects from uplead.com. All fields typed and schema-versioned.
"domain": "acmecorp.com", "tech_category": "Marketing Automation", "tech_name": "HubSpot", "tech_vendor": "HubSpot Inc", "last_detected": "2026-05-12", "usage_status": "Active"
| # | domain | tech_category | tech_name | tech_vendor | first_detected | last_detected |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Public Employees objects from uplead.com. All fields typed and schema-versioned.
"domain": "acmecorp.com", "employee_name": "Jane Doe", "job_title": "VP of Engineering", "department": "Engineering", "seniority_level": "VP", "location": "San Francisco, CA"
| # | domain | employee_name | job_title | department | seniority_level | linkedin_url |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Firmographics objects from uplead.com. All fields typed and schema-versioned.
"domain": "acmecorp.com", "funding_total": "120000000", "last_funding_type": "Series C", "sic_code": "7372", "naics_code": "511210", "ownership_type": "Private"
| # | domain | funding_total | last_funding_date | last_funding_type | investors | sic_code |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Web Presence objects from uplead.com. All fields typed and schema-versioned.
"domain": "acmecorp.com", "linkedin_url": "linkedin.com/company/acmecorp", "twitter_url": "twitter.com/acmecorp", "organic_traffic": 125000, "ad_spend": "10k-50k", "seo_keywords": "['enterprise software', 'b2b saas']"
| # | domain | linkedin_url | twitter_url | facebook_url | alexa_rank | organic_traffic |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our UpLead scraper handles complex directory structures, JavaScript rendering, and strict rate limits to extract public company intelligence and firmographics without manual export limits.
Capture company name, domain, employee count, revenue estimates, and year founded across millions of directory profiles.
Extract technology usage signals, vendor categorisation, and estimated tech spend parameters linked to target domains.
Scrape public employee directory listings including job titles, departments, seniority levels, and location data.
Normalise SIC codes, NAICS codes, and UpLead proprietary industry categorisations for accurate segmentation.
Track total funding amounts, recent round types, and investor lists associated with private companies.
Extract associated social media profiles, organic traffic estimates, and SEO keyword indicators.
Receive only updated records when companies change headcount, add new technology, or raise capital.
Filter and extract companies based on HQ location, regional office presence, or operating markets.
Configure continuous extraction pipelines at weekly or monthly cadences to keep your CRM data fresh.
Brief in. Clean data out.
Provide target domains, industry parameters, or company size filters. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, session management, and rate-limit handling.
Schema validation, null-rate checks, and sample profile reviews before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
B2B directories deploy aggressive rate limiting and bot protection. Here is how we maintain extraction throughput.
Directory sites monitor TLS fingerprints and IP reputation. Our crawlers use residential ISP proxies with realistic browser fingerprints and randomised request timing to simulate normal user behaviour.
Aggressive scraping triggers IP bans. We distribute requests across thousands of nodes using token-bucket algorithms to stay strictly below target rate limits while maintaining high overall throughput.
Profile data often loads asynchronously. We run full Playwright browser sessions with JavaScript execution and lazy-load triggering to capture data that headless HTTP clients miss entirely.
Our selector strategy uses multiple fallback chains per field, including CSS selectors, XPath, and text-pattern matching, ensuring minor layout changes do not break your data pipeline.
For large company catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Strategy teams size markets by extracting companies fitting specific revenue, headcount, and industry criteria.
Product marketers track competitor technology stacks, funding rounds, and headcount growth over time.
Growth teams build targeted account lists based on firmographics and technographics for outbound campaigns.
Revenue operations teams automatically update stale Salesforce or HubSpot records with fresh company data.
Venture capital and private equity firms track company growth signals to identify potential investment targets.
Sales leadership maps account distribution by region, industry, and size to optimise rep territories.
"UpLead contains highly structured firmographic and tech stack data, but manual list building limits your engineering velocity and CRM enrichment pipelines."
Extracting B2B intelligence at scale requires bypassing sophisticated anti-bot measures, managing IP reputation, and maintaining selector chains across frequent DOM updates. DataFlirt absorbs that complexity so your revenue operations teams can focus on targeting rather than data infrastructure.
Everything supported by our uplead.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. Combined via middleware for optimal throughput.
We maintain pools of residential ISP proxies. Rotation happens per request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About uplead.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from directory sites is generally permissible under applicable law. DataFlirt targets only public, non-authenticated company profiles and firmographic data. We do not circumvent authentication walls or extract gated contact information without client credentials. Clients should review terms of service and consult legal counsel.
No, unless you provide authenticated session credentials with sufficient paid credits. We focus on extracting the public directory data: company firmographics, tech stacks, and public employee titles. Gated contact data requires a premium UpLead subscription.
We use residential ISP proxies, full Playwright browser sessions, and request timing modelled on human behaviour. We distribute requests across a wide IP pool to stay well below the threshold that triggers bot detection or IP bans.
Data freshness depends on your pipeline configuration. We can run continuous extraction pipelines at weekly or monthly cadences to ensure your CRM or data warehouse always has the latest headcount and tech stack signals.
Yes. The extracted tech stack data includes the technology name, vendor, and broad category classification, allowing you to segment companies based on their existing software usage.
Our smallest packages start at a defined list of target domains or industry filters with weekly delivery. For larger catalogues or custom schema requirements, we price based on volume and delivery frequency.
Absolutely. We provide a sample run of up to 500 company profiles as part of the pre-engagement scoping process so you can validate schema fit and data quality before signing a contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off TAM export or continuous CRM enrichment feeds, we scope, build, and operate the pipeline. Tell us what you need.
