We extract company profiles, financial statements, director networks, and corporate structures from Duedil. Delivered as clean JSON, CSV, or Parquet to S3 or PostgreSQL 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 duedil.com. All fields typed and schema-versioned.
"company_name": "ACME HOLDINGS LTD", "company_number": "01234567", "status": "Active", "incorporation_date": "2014-06-12", "company_type": "Private limited with Share Capital", "registered_address": "123 Business Road, London, EC1A 1BB", "sic_codes": "['62012', '62020']", "employee_count": 245
| # | company_name | company_number | status | incorporation_date | company_type | registered_address |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Financial Statements objects from duedil.com. All fields typed and schema-versioned.
"company_number": "01234567", "year_ending": "2025-12-31", "turnover": 45200000.0, "gross_profit": 18500000.0, "operating_profit": 4200000.0, "net_assets": 12400000.0, "cash_at_bank": 3100000.0, "filing_date": "2026-09-14"
| # | company_number | year_ending | turnover | gross_profit | operating_profit | net_assets |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Director Networks objects from duedil.com. All fields typed and schema-versioned.
"director_id": "DIR-987654321", "director_name": "Jane Doe", "role": "Director", "appointed_date": "2018-03-01", "date_of_birth": "1975-08", "nationality": "British", "active_appointments": 3, "total_appointments": 7
| # | director_id | director_name | role | appointed_date | resigned_date | date_of_birth |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Corporate Structure objects from duedil.com. All fields typed and schema-versioned.
"company_number": "01234567", "parent_company": "ACME GROUP PLC", "ultimate_parent": "GLOBAL HOLDINGS INC", "subsidiaries_count": 4, "ownership_percentage": 100.0, "shareholder_name": "ACME GROUP PLC", "share_class": "Ordinary", "shares_held": 10000
| # | company_number | parent_company | ultimate_parent | subsidiaries_count | ownership_percentage | shareholder_name |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Credit & Risk objects from duedil.com. All fields typed and schema-versioned.
"company_number": "01234567", "credit_score": 85, "credit_limit": 250000.0, "risk_band": "Low Risk", "days_beyond_terms": 12, "ccj_count": 0, "ccj_total_value": 0.0, "mortgage_charges": 2
| # | company_number | credit_score | credit_limit | risk_band | days_beyond_terms | ccj_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Duedil scraper extracts complex corporate entity data: deep financial histories, director cross-appointments, and ultimate beneficial ownership structures, delivered as clean relational data.
Extract registered address, trading addresses, SIC codes, employee brackets, and contact details.
Capture 10-year P&L, balance sheet, and cash flow statements filed at Companies House.
Track active and resigned directors, secretaries, and their cross-board appointments.
Identify Ultimate Beneficial Owners and cap table structures with ownership percentages.
Map parent companies, subsidiaries, and joint ventures across complex international groups.
Extract credit scores, suggested credit limits, and risk band classifications.
Monitor County Court Judgments, active charges, and satisfied mortgages.
Track status changes, new director appointments, or recent financial filings.
Run continuous pipelines at monthly or quarterly cadences to capture latest filings.
Brief in. Clean data out.
Provide company numbers, SIC codes, or revenue brackets. We design the extraction schema.
We configure Scrapy crawlers, proxy rotation, and session management for duedil.com.
Schema validation, null-rate checks, and financial data integrity tests before full launch.
JSON / CSV / Parquet pushed to your S3 bucket or PostgreSQL database on agreed cadence.
Extracting structured financial data from business directories requires handling diverse table formats and strict rate limits.
Duedil monitors request volumes and IP reputation. We route traffic through UK-based residential proxies to maintain access and avoid rate limits.
Extracting deep financial histories requires authenticated sessions. We manage credential pools and cookie rotation to prevent account bans.
Financial tables vary wildly by company size and filing type. Our selectors normalise these structures into consistent schemas.
We respect platform rate limits by distributing requests across hundreds of concurrent workers with random jitter.
Financial data requires strict typing. We validate all numerical fields and cross-check totals before delivery.
Sales teams use firmographic and financial filters to identify high-growth target accounts.
Lenders ingest financial histories and CCJ records to automate initial credit scoring models.
Enterprise data teams enrich internal CRM records with canonical registered addresses and SIC codes.
Compliance officers map director networks and UBOs to identify conflicts of interest or sanctioned entities.
Analysts aggregate sector-level financial performance using SIC codes and turnover data.
Strategy teams monitor rival company filings, subsidiary creation, and director movements.
"Duedil aggregates the UK corporate landscape into a single view, but extracting that network graph requires serious infrastructure."
Most teams underestimate the complexity of scraping financial data. Normalising inconsistent table structures, managing authenticated sessions, and handling pagination across complex corporate trees requires dedicated engineering. DataFlirt manages the extraction pipeline so your data scientists can focus on modelling risk and opportunity.
Everything supported by our duedil.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. Playwright handles JavaScript rendering for dynamic charts.
We maintain pools of UK-based residential IPs to ensure high success rates and low latency.
Pipelines run on AWS ECS. Airflow handles scheduling. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About duedil.com scraping, legality, and pipeline operations.
Ask us directly →Scraping public company data is generally permissible. We target unauthenticated and authenticated data per client requirements, ensuring compliance with UK data protection regulations.
We use distributed crawling, UK residential proxies, and request jitter to stay within acceptable request thresholds and avoid IP bans.
Yes. We can seed the pipeline with specific industry codes, revenue brackets, or geographical regions.
We can schedule pipelines to run daily, capturing new Companies House filings as soon as they are processed by Duedil.
Yes. We capture current and historical directorships, including cross-board appointments and resignation dates.
Yes. We provide a sample run of 100 company profiles during the scoping phase to validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a full UK corporate database export or targeted daily financial updates, we build and manage the infrastructure.
