# Scrape HNW in the UK (`belcaidsaad/hnw-uk-pipeline`) Actor HNW UK — Find British Millionaires by Name, Every Morning. - **URL**: https://apify.com/belcaidsaad/hnw-uk-pipeline.md - **Developed by:** [Saad Belcaid](https://apify.com/belcaidsaad) (community) - **Categories:** Automation, Jobs, Other - **Stats:** 6 total users, 6 monthly users, 25.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## HNW UK — Find British Millionaires by Name, Every Morning **Built for Haris King (SSM) by [Saad Belcaid](https://www.skool.com/@saadbelcaid).** This scraper finds UK millionaires. By name. With the company they own. With a one-line reason to call them today. --- ### The dumb-simple version Every morning, the UK Government publishes the financial accounts of thousands of British companies — for free. Inside those filings: profit, turnover, who owns the shares. This scraper reads all of it. Then it answers one question: **"Whose company made enough profit last year that this person is now rich?"** It outputs a list. One row per rich person. Their name. Their company. Roughly how rich. And one line that says why now. Three things you should know: 1. **Same profit, different wealth.** A £2M-profit software business makes its 75% owner ~£14M rich. A £2M-profit restaurant makes them ~£5M. Identical profit. The difference is what the market pays per £1 of profit in that industry — 8× for software, 3.5× for restaurants. Industry is the dial. 2. **The signal is the filing.** When a company files fresh accounts, that owner's wealth just got re-papered today. That's why the row exists — not last year, not last month, today. 3. **Ceased = freshly liquid.** When someone *was* a major owner but no longer is, they sold. They got cash. They're in money-decision mode. The scraper surfaces them too — you'll find these in the column `psc_status = ceased`. Most lead-gen actors throw these away. We don't. UK only. Free data only. No browsers, no proxies, no AI in the hot path. --- ### Max-value playbook (do this in order) #### Day 1 — first run, get volume ```yaml companiesHouseApiKey: backfillDays: 14 ## process the last 2 weeks of filings in one run minPersonalWealth: 5000000 ## default £5M floor ## everything else: defaults ```` Hit run. Wait ~15 min. Expect **200–500 rows** in your dataset. That's your first batch. #### Day 1, hour 2 — triage by signal type Open the dataset. Sort or filter by `psc_status`. Three lists, in this order: | List | Filter | Why first | |---|---|---| | **Hot — fresh exits** | `psc_status = ceased` AND `ceased_on` in last 12 months | They sold, they got paid, they're picking advisors *right now*. **Call this week.** | | **Warm — top wealth band, decision-makers** | `estimated_personal_wealth_band ∈ {£25M+, £50M+, £100M+}` AND `ownership_band = 75-100%` | Top of the pyramid. Sole/majority owners are the decision-maker, not a junior partner. Call within the month. | | **Steady — your industry, sole/majority** | `targetSicPrefixes = your sector` AND `ownership_band ∈ {50-75%, 75-100%}` | Bread-and-butter. Sequence them across your normal cadence. | #### Day 2 onwards — daily drip ```yaml companiesHouseApiKey: backfillDays: 0 ## today only ## everything else: same defaults ``` Set up a Schedule with cron `0 8 * * 2-6` (8am UTC, Tue–Sat). The actor's persistent dedup means **only NEW people surface every morning** — typically 10–40 fresh leads per day. Steady drip into your CRM with zero overlap with yesterday's batch. *** ### Filter recipes (copy-paste) #### "I want freshly-liquid Brits this month" ```yaml pscStatus: ceased ukResidentOnly: true backfillDays: 30 minPersonalWealth: 5000000 ``` #### "I want central London £10M+ founders" ```yaml wealthBands: ["£10M+", "£25M+", "£50M+", "£100M+"] ownershipBands: ["75-100%", "50-75%"] regionPostcodePrefixes: ["SW", "W1", "EC", "WC", "N1", "NW1"] ``` #### "I want UK SaaS / IT founders" ```yaml targetSicPrefixes: ["62", "63"] ownershipBands: ["75-100%"] minPersonalWealth: 5000000 ``` #### "I want pharma / biotech / healthcare sellers (recent exits)" ```yaml targetSicPrefixes: ["21", "72", "86", "87"] pscStatus: ceased backfillDays: 60 ``` #### "I only care about ultra-HNW (£25M+)" ```yaml minPersonalWealth: 25000000 ownershipBands: ["75-100%", "50-75%"] ``` #### "I want Manchester / NW England HNW" ```yaml regionPostcodePrefixes: ["M", "BL", "OL", "SK", "WN"] ``` #### "I want Scottish HNW" ```yaml regionPostcodePrefixes: ["EH", "G", "AB", "DD", "PA", "FK", "KY", "ML"] ``` *** ### Why "ceased = gold" deserves its own paragraph Most actors filter ceased PSCs as "old data." They drop them. We don't. A ceased PSC is someone who held significant control of a profitable UK business and **no longer does**. There's basically one reason that happens: they sold. And in the 6–18 months after a sale, that person is doing every one of these things: - Picking a new wealth manager - Buying property (sometimes multiple) - Setting up a family office or trust structure - Looking at their next venture or angel deals - Giving to charity strategically (tax-driven) - Restructuring inheritance plans If you sell **any** of those services — wealth management, real estate, tax/legal, M\&A advisory, charity advisory, business consulting, executive coaching, family office services — ceased PSCs from the last 12–18 months are the **warmest lead category in your dataset**. Not just warm — time-sensitive. Their decisions get made, they sign with someone, and the window closes. Use `pscStatus: ceased` + filter the dataset by `ceased_on` year ≥ (this year − 1). That's your urgent-call list. *** ### Output — one row per HNW individual Every row has these fields. The ones in **bold** are the ones you'll use most. | Field | Example | |---|---| | **`person_name`** | John Smith | | **`psc_status`** | `active` (still owns) or `ceased` (sold — call urgently) | | `psc_relationship` | `direct` (PSC of this co) or `via_chain` (PSC of a parent holdco) | | **`ceased_on`** | `2024-07-06` (date they exited, if `ceased`) | | `nationality` | British | | `country_of_residence` | United Kingdom | | **`ownership_band`** | `75-100%` | | `control_summary` | "ownership of shares 75 to 100 percent, voting rights 75 to 100 percent" | | `holding_chain` | `["Acme Holdings", "Acme Topco"]` (set when discovered through a parent chain) | | **`company_name`** | Acme Software Ltd | | `company_number` | 12345678 | | **`registered_address`** | 123 High Street, Manchester, M1 1AA | | `locality` | Manchester | | `postal_code` | M1 1AA | | `country` | England | | **`sic_codes`** | `["62012"]` | | **`sic_descriptions`** | `["Business and domestic software development"]` | | `industry_multiple_applied` | `8.0` | | **`company_ebitda`** | 4,200,000 | | `company_turnover` | 18,500,000 | | `company_employees` | 45 | | **`estimated_personal_wealth`** | 29,400,000 | | **`estimated_personal_wealth_band`** | £25M+ | | **`signal`** | "Majority/sole owner of Acme Software Ltd — business and domestic software development, £4.2M EBITDA, fresh filing 2026-04-29" | | `filing_date` | 2026-04-29 | #### `direct` vs `via_chain` When you see the same person in two rows for two related companies (e.g. an operating co AND its holding co), one row will be `direct` and the other `via_chain`. The `direct` row is the canonical one — it's where the person is actually listed as PSC. The `via_chain` row was found by tracing through ownership. Keep both for full coverage; or filter `psc_relationship = direct` to de-double-count. *** ### How we estimate wealth (in plain English) One rule. Three inputs. No AI, no magic. ``` wealth = profit × industry multiple × % they own ``` Translated: > "How much profit did the business make × how much someone would pay to buy a business like that × what slice of it this person owns." That's the back-of-envelope every UK M\&A advisor scribbles before they pick up the phone. It's not a valuation. It's a triage signal — good enough to know who's worth calling. #### What's a "multiple"? (the SIC story) When someone buys a private business, they pay a multiple of its yearly profit. **Software gets 8×. Restaurants get 3.5×.** Why? Because software profit is recurring and scalable. Restaurant profit shows up if you're standing in the kitchen at 11pm. The market knows the difference and pays accordingly. To pick the right multiple per company, we use the company's **SIC code** — the UK Government's industry tag, declared on every annual filing (5 digits, e.g. `62012` = software, `56101` = restaurants). The scraper matches the SIC code against an internal table of **~85 industry prefixes** and uses the most specific match. #### Same profit, very different millionaire | Owner | Industry | Profit | Multiple | Stake | Estimated wealth | |---|---|---|---|---|---| | Software founder | 62012 (software) | £2M | 8× | 75% | **£14M → £10M+ band** | | Restaurateur | 56101 (restaurant) | £2M | 3.5× | 75% | **£5.25M → £5M+ band** | | Restaurateur (50% partner) | 56101 (restaurant) | £2M | 3.5× | 37.5% | **£2.6M → £1M+ band, dropped** | Identical revenue. Identical profit. The difference is which industry they're in and how much they own. #### Industry multiples — selected examples (Full coverage of ~85 SIC prefixes lives in `src/wealth.py`. Lookup matches the LONGEST prefix, so `62012` software gets 8× even though `62` IT services is 6.5×.) | Sector | Multiple | Why | |---|---|---| | Biotech / pharma R\&D (`7211`) | 9.0× | IP-heavy, clinical assets, pharma buyer demand | | Fund management (`6630`) | 8.5× | Recurring AUM fees, sticky | | Software development (`6201`) | 8.0× | SaaS scaling economics | | Insurance brokers (`6622`) | 8.0× | Subscription-like renewals | | Pharma manufacturing (`21`) | 8.0× | Regulated, branded | | Data / cloud / hosting (`6311`) | 7.5× | Cloud-services premium | | Specialist medical / dental (`8622`, `8623`) | 7.5× | Private healthcare consolidation | | Hospitals (`861`) | 7.0× | Recurring care revenue | | Insurance (`65`) | 7.5× | High recurrence | | Veterinary (`75`) | 7.0× | Active consolidation play | | Medical instruments (`3250`) | 7.0× | High-margin specialty mfg | | Pre-primary education (`8510`) | 7.0× | Nursery roll-up trend | | IT consultancy (`6202`) | 6.5× | Tech services premium | | Banking (`641`) | 5.5× | Regulated, capital-heavy | | Mgmt consultancy (`7022`) | 6.0× | Repeat-engagement | | Real-estate letting (`6820`) | 5.5× | Rental recurrence | | Wholesale (`46`) | 4.5× | B2B recurrence | | Manufacturing (general) (`28`, `29`) | 5.5× | Capital-heavy operations | | Construction (`41`–`43`) | 4.0–4.5× | Project-based, cyclical | | Retail (`47`) | 4.0× | Margin pressure | | Restaurants (`56`) | 4.0× | Fixed-cost squeeze | | Pubs (`5630`) | 3.5× | Toughest | | **Default fallback** | **4.0×** | Used when SIC isn't in the table | These are **conservative**. Real M\&A deals trade above and below these depending on growth, recurrence, scale, customer concentration. We tune low on purpose — the doctrine is **under-estimate wealth, never over-estimate**. A £14M owner-operator on this scoring is, in reality, almost always richer than that. #### Ownership-band midpoints (from Companies House PSC API) | Band | What we use | |---|---| | 75–100% | 0.875 | | 50–75% | 0.625 | | 25–50% | 0.375 | Companies House only reports owners who hold **at least 25%** of the shares or voting rights. Anyone who shows up holds at least a quarter of the company. #### Wealth bands the scraper emits `<£1M`, `£1M+`, `£5M+`, `£10M+`, `£25M+`, `£50M+`, `£100M+` The default floor is **£5M**. Raise it to `£10M+` if you only want serious money. Drop it to `£1M+` if you want a wider net of owner-operators. Or use `wealthBands` to keep specific bands only. *** ### Input options | Field | Default | Description | |---|---|---| | `companiesHouseApiKey` | *(required)* | Free REST key from CH developer portal | | **Wealth filters** | | | | `minPersonalWealth` | `5000000` | Wealth floor in £ | | `wealthBands` | `[]` | Restrict to bands. e.g. `["£25M+","£50M+","£100M+"]` | | `ebitdaPreThreshold` | `0` | Auto-derived from `minPersonalWealth` when `0`. Override only for tuning. | | **Person filters** | | | | `ownershipBands` | `[]` | e.g. `["75-100%"]` for sole/majority owners only | | `pscStatus` | `all` | `active` / `ceased` / `all`. Use `ceased` for fresh-exit lists. | | `ukResidentOnly` | `false` | Drop non-UK residents | | **Geographic filter** | | | | `regionPostcodePrefixes` | `[]` | e.g. `["SW","W1","EC"]` for central London | | **Industry filters** | | | | `targetSicCodes` | `[]` | Exact 5-digit SIC matches | | `targetSicPrefixes` | `[]` | SIC prefixes, e.g. `["62"]` for IT | | **Date range** | | | | `backfillDays` | `0` | Process last N days in addition to today (max 60) | | `bulkFileDate` | *(today)* | Override the end date `YYYY-MM-DD` | | **Advanced** | | | | `maxCorporatePscHops` | `3` | How deep to trace holding-co ownership chains | | `skipWeekendCheck` | `false` | Run anyway on Sun/Mon (no-op since CH won't have published) | *** ### Use cases by industry #### Wealth-management & private-banking outreach `minPersonalWealth: 10000000` + `pscStatus: ceased` for the past 12 months. These are the people picking a new advisor right now. #### Estate planning / tax / legal `minPersonalWealth: 25000000` + `ownershipBands: ["75-100%"]`. Patient outreach, but high-LTV. #### Family offices `minPersonalWealth: 50000000` + `pscStatus: all`. UK ultra-HNW universe is ~12,000 individuals; this surfaces the ones whose wealth is fresh-papered today or who just exited. #### Real estate / property advisory `pscStatus: ceased` + `regionPostcodePrefixes` matching where you sell. Recent exits buy second/third homes; they self-identify by location. #### Connector OS Station Pipe the dataset into Station as the demand side. The `signal` field plugs straight into the I Layer for evaluation against your supply network (advisors, brokers, vendors). **Flow:** scrape → dataset → paste dataset ID into Station → match against your supply → scored introductions. *** ### How it works under the hood - Parses XBRL filings using the UK Government's own [`stream-read-xbrl`](https://github.com/uktrade/stream-read-xbrl) - EBITDA = operating profit + depreciation (conservative floor estimate) - Rate-limited to stay within Companies House's 600 req/5min limit - Normalizes UK CH company numbers (zero-pad, strip prefixes) so malformed bulk-feed values don't lose leads - Resolves corporate PSC chains by `registration_number`, falling back to exact-name search when CH didn't store the number — so PE/holdco structures still surface real humans - Tags each row `direct` vs `via_chain` so operators can de-double-count when an operating co AND its holdco both file separately - Surfaces both **active** and **ceased** PSCs — the ceased ones are the highest-value HNW signal in the dataset - Strips honorifics (`Mr/Mrs/Dr/Sir`) before deduping so the same person doesn't appear under multiple titles - Stores `(person + company)` keys in a persistent KV store so duplicates never reappear day-over-day *** ### Costs - Companies House API: **free** (600 req / 5 min) - Apify compute: ~10–15 min per run × 1024 MB ≈ trivial CU on the standard plan - Multi-day backfill (`backfillDays > 0`): N× the per-day cost *** *Built by Saad Belcaid for Haris King's SSM workflow. Data sourced from Companies House (public record). Wealth estimates are heuristic, not valuations.* # Actor input Schema ## `companiesHouseApiKey` (type: `string`): Free REST API key from https://developer.company-information.service.gov.uk/. Not the OAuth client secret. ## `minPersonalWealth` (type: `integer`): Only emit individuals at or above this estimated wealth (EBITDA × industry multiple × ownership %). Default £5M. ## `wealthBands` (type: `array`): Restrict output to specific wealth bands. Empty = all bands above the minimum. Pick from: £1M+, £5M+, £10M+, £25M+, £50M+, £100M+ ## `ebitdaPreThreshold` (type: `integer`): Skip companies below this EBITDA before any API enrichment. Leave at 0 to auto-derive from your minimum personal wealth (recommended). ## `ownershipBands` (type: `array`): Only emit individuals in these ownership bands. Empty = all. Pick from: 25-50%, 50-75%, 75-100% ## `pscStatus` (type: `string`): active = current owners only. ceased = recent exits only (people who just sold and got paid — fresh liquidity). all = both, with each row labeled. ## `ukResidentOnly` (type: `boolean`): Drop individuals whose country of residence is not UK / England / Scotland / Wales / Northern Ireland. ## `regionPostcodePrefixes` (type: `array`): Restrict to companies registered at these UK postcode prefixes. e.g. \['SW','W1','EC'] for central London, \['M'] for Manchester, \['EH'] for Edinburgh. Empty = whole UK. ## `targetSicCodes` (type: `array`): Only include companies with these exact 5-digit SIC codes. Empty = all sectors. ## `targetSicPrefixes` (type: `array`): Match SIC code prefixes. e.g. \['62'] for IT/software, \['64','65','66'] for finance, \['86','87'] for healthcare. ## `backfillDays` (type: `integer`): Process the last N days of filings in addition to today. 0 = today only. 7 = past week. Useful for the first run when you want volume. ## `bulkFileDate` (type: `string`): Override the end date (YYYY-MM-DD). Defaults to today. Combine with backfillDays to re-process a historical window. ## `maxCorporatePscHops` (type: `integer`): How deep to trace holding-company ownership chains. 3 covers most UK corporate structures. ## `skipWeekendCheck` (type: `boolean`): Run even on Sun/Mon (CH won't have published, but useful for testing the actor end-to-end). ## Actor input object example ```json { "minPersonalWealth": 5000000, "wealthBands": [], "ebitdaPreThreshold": 0, "ownershipBands": [], "pscStatus": "all", "ukResidentOnly": false, "regionPostcodePrefixes": [], "targetSicCodes": [], "targetSicPrefixes": [], "backfillDays": 0, "maxCorporatePscHops": 3, "skipWeekendCheck": false } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("belcaidsaad/hnw-uk-pipeline").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("belcaidsaad/hnw-uk-pipeline").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call belcaidsaad/hnw-uk-pipeline --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=belcaidsaad/hnw-uk-pipeline", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Scrape HNW in the UK", "description": "HNW UK — Find British Millionaires by Name, Every Morning.", "version": "0.1", "x-build-id": "FubEIttFO5222fBpD" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/belcaidsaad~hnw-uk-pipeline/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-belcaidsaad-hnw-uk-pipeline", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/belcaidsaad~hnw-uk-pipeline/runs": { "post": { "operationId": "runs-sync-belcaidsaad-hnw-uk-pipeline", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/belcaidsaad~hnw-uk-pipeline/run-sync": { "post": { "operationId": "run-sync-belcaidsaad-hnw-uk-pipeline", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "companiesHouseApiKey" ], "properties": { "companiesHouseApiKey": { "title": "Companies House API Key", "type": "string", "description": "Free REST API key from https://developer.company-information.service.gov.uk/. Not the OAuth client secret." }, "minPersonalWealth": { "title": "Minimum Estimated Personal Wealth (£)", "minimum": 0, "type": "integer", "description": "Only emit individuals at or above this estimated wealth (EBITDA × industry multiple × ownership %). Default £5M.", "default": 5000000 }, "wealthBands": { "title": "Wealth Bands (filter)", "type": "array", "description": "Restrict output to specific wealth bands. Empty = all bands above the minimum. Pick from: £1M+, £5M+, £10M+, £25M+, £50M+, £100M+", "items": { "type": "string" }, "default": [] }, "ebitdaPreThreshold": { "title": "EBITDA Pre-Threshold (£) — advanced", "minimum": 0, "type": "integer", "description": "Skip companies below this EBITDA before any API enrichment. Leave at 0 to auto-derive from your minimum personal wealth (recommended).", "default": 0 }, "ownershipBands": { "title": "Ownership Bands (filter)", "type": "array", "description": "Only emit individuals in these ownership bands. Empty = all. Pick from: 25-50%, 50-75%, 75-100%", "items": { "type": "string" }, "default": [] }, "pscStatus": { "title": "PSC Status", "enum": [ "all", "active", "ceased" ], "type": "string", "description": "active = current owners only. ceased = recent exits only (people who just sold and got paid — fresh liquidity). all = both, with each row labeled.", "default": "all" }, "ukResidentOnly": { "title": "UK Residents Only", "type": "boolean", "description": "Drop individuals whose country of residence is not UK / England / Scotland / Wales / Northern Ireland.", "default": false }, "regionPostcodePrefixes": { "title": "Region — Postcode Prefixes", "type": "array", "description": "Restrict to companies registered at these UK postcode prefixes. e.g. ['SW','W1','EC'] for central London, ['M'] for Manchester, ['EH'] for Edinburgh. Empty = whole UK.", "items": { "type": "string" }, "default": [] }, "targetSicCodes": { "title": "Industry — Exact SIC Codes", "type": "array", "description": "Only include companies with these exact 5-digit SIC codes. Empty = all sectors.", "items": { "type": "string" }, "default": [] }, "targetSicPrefixes": { "title": "Industry — SIC Prefixes", "type": "array", "description": "Match SIC code prefixes. e.g. ['62'] for IT/software, ['64','65','66'] for finance, ['86','87'] for healthcare.", "items": { "type": "string" }, "default": [] }, "backfillDays": { "title": "Backfill Days", "minimum": 0, "maximum": 60, "type": "integer", "description": "Process the last N days of filings in addition to today. 0 = today only. 7 = past week. Useful for the first run when you want volume.", "default": 0 }, "bulkFileDate": { "title": "Bulk File Date Override", "type": "string", "description": "Override the end date (YYYY-MM-DD). Defaults to today. Combine with backfillDays to re-process a historical window." }, "maxCorporatePscHops": { "title": "Max Corporate PSC Hops", "minimum": 0, "maximum": 10, "type": "integer", "description": "How deep to trace holding-company ownership chains. 3 covers most UK corporate structures.", "default": 3 }, "skipWeekendCheck": { "title": "Skip Weekend Check", "type": "boolean", "description": "Run even on Sun/Mon (CH won't have published, but useful for testing the actor end-to-end).", "default": false } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```