Company records are corporate facts. Officer records are real people with birth months and correspondence addresses, and they need treating that way.
ScrapeIt runs the collection as a managed service. You name the companies, sectors or filters; we use the registrar's free interface where it covers the need, extract filed accounts where it does not, mark personal data fields explicitly, and hand back CSV, JSON, Excel or a push into your warehouse.
Where a company-level dataset would meet the brief we propose that version, because it is cheaper for you and carries no personal data obligations at all.
This is a statutory public register and we collect it politely. Officer and control records describe living individuals, and you are the controller of whatever you build from them. Your counsel should see the use case before the project starts - that is not a formality on this source.
Company records carry the company number, name, previous names, status, type, incorporation date, registered office address, SIC codes, accounts and confirmation statement dates.
The company number is the identifier everything joins on. Names change and are reused; the number does not, and a dataset matched on name will merge unrelated companies and split renamed ones.
Officer records carry the name as filed, role, appointment and resignation dates, nationality, occupation and the partial date of birth the register publishes. These describe identified living people and the dataset marks them as such, because what happens downstream to a personal data column should be a deliberate decision rather than an oversight.
Persons with significant control are collected as their own record type, with the nature of control as published.
Document records carry the filing type, date and address, with extracted content where a client needs the accounts as numbers rather than as files.
Accounts extraction is the substantial technical work here. Filed accounts exist as documents in varying formats and turning them into comparable figures across thousands of companies is a real pipeline, not a download.
Directorship network analysis - which people sit on which boards and how companies connect through shared officers - is the most requested analytical product and the one that most clearly needs the personal data conversation first, because a network of named individuals is exactly the kind of profiling that carries obligations.
Status and filing monitoring is the lighter product: which companies changed status, filed late or moved to dissolution, built from company-level fields with no personal data involved at all. Where a brief can be met this way we suggest it.
Limits stated plainly: we pace politely on a public service, we use the free interface where it fits, and we raise the personal data question at scoping every time rather than treating the statutory publication as the end of the matter.
Companies House is the UK registrar of companies. Its public service publishes company records, filing histories, accounts, officer appointments and persons with significant control, for every registered company in the United Kingdom.
It also runs a free public programmatic interface with its own developer portal, which covers company profiles, officers, filing history and search. For most briefs that interface is the right route, and a scraping project that ignores it is solving a problem the registrar already solved.
Where collection still has a role is in the documents. Filed accounts and certain statements exist as documents rather than as structured fields, and extracting their contents into data is work the interface does not do for you.
The search and company pages respond directly. There is no robots file at the service address, which we take as no stated restriction rather than as an invitation, and we pace accordingly.
Get a Quote
Developers
Customers worldwide
Pages extracted
Hours saved for our clients
€199 / one-time
setup fee - included
€169 / mo
setup fee €499
€229 / mo
setup fee €499
€349 / mo
setup fee €499
€549 / mo
setup fee €799
This register is public by statute, and that is often where the thinking stops. It should not.
Company records are corporate facts and carry no personal data question. Officer records are different: a name, a role, a nationality, an occupation, a month and year of birth and a correspondence address, describing a living person. The register publishes them under a legal regime designed for transparency about who controls companies. That is not the same thing as a general permission to compile them into profiles for any purpose.
In practice the client is the controller of whatever they build, and the obligations that follow - purpose, retention, the rights of the people in the dataset - are theirs. Our part is to make the personal data visible as such in the schema rather than letting it arrive as just more columns, and to raise the question at scoping rather than after delivery.
The second reason to think before collecting is scope. A great many briefs that ask for all officers actually need officers of a specific set of companies, and the narrower version is both cheaper and much easier to defend.
The third is that the free interface already covers most of it, which means the conversation is usually about what a client should build rather than whether we can fetch it.
Learn how to use web scraping to solve data problems for your organization
Leveraging advances in technology, the AI-powered web scraper has skyrocketed in demand and is helping to expand capabilities by automating tedious daily tasks and speeding up data collection from thousands of websites several times over.
Web scraping is a method of obtaining web data by extracting it from pages of web resources with the help of a program, that is, in automatic mode. It is used to syntactically convert web pages into more usable forms.
If you specialize in machine learning, you need to feed large amounts of data to the algorithms. Web scraping is the easiest and the most efficient method of collecting the data from all over the Internet.
ScrapeIt is a managed extraction company, not a tool you have to learn. Our team builds the pipeline, maintains accounts extraction as filing formats change, and repairs it before a monitoring series misses a status change.
You see a sample first, in your format, over the companies you actually track, with personal data fields marked so the decision about them is one you make knowingly.
For most briefs, yes, and we will say so. The registrar runs a free public interface covering profiles, officers, filings and search. Collection earns its place on the filed documents, which the interface hands you as files rather than as data.
Because public by statute and free to compile for any purpose are different things. Officer records describe living people, and whatever you build makes you the controller with the obligations that follow. We surface it at scoping rather than after delivery.
Yes, and it is the product that most needs the conversation above first. A network of named individuals across boards is precisely the kind of profiling that carries obligations, so we scope it deliberately rather than as a side effect.
Yes, and we often propose it: company-level fields only - status, filings, accounts, addresses, SIC codes. Many briefs asking for everything actually need this, and it is cheaper and carries no personal data obligations.
Because filed accounts are documents in varying formats rather than structured fields. Turning them into figures comparable across thousands of companies is a real pipeline, and it is the part of this source where collection genuinely adds something.
Step 1 - Make a Request
You share your needs, expectations, and desired timeframe. We’ll suggest the best solution based on your request and budget.
Step 2 - Configuring Custom Web Crawlers
Our specialists configure the crawlers and extract a sample dataset for your review before proceeding with the full-scale extraction.
Step 3 - Collect and Deliver
Once you approve the sample, we launch the project and start full data collection. We gather, filter, and structure the data for easy use, delivering it on time in your preferred format.
Step 4 - Maintain and Support
Our team manages ongoing processes, monitors website changes, and supports all data extraction cycles. We can also help integrate data into your systems or create dashboards to simplify analysis.
Scrapeit Sp. z o.o.
10/208 Legionowa str., 15-099, Bialystok, Poland
NIP: 5423457175
REGON: 523384582
