# Startup Funding & Investor Intel - Form D Rounds, Investors (`seibs.co/startup-funding-intel`) Actor Fresh startup funding rounds and investor intel synthesized from SEC Form D filings, EDGAR full-text search, and press coverage. A Crunchbase-style feed rebuilt from primary sources. For VC/PE deal sourcing, B2B sales (a fresh raise = budget), and recruiters. Public data only. - **URL**: https://apify.com/seibs.co/startup-funding-intel.md - **Developed by:** [Seibs.co](https://apify.com/seibs.co) (community) - **Categories:** Business, Lead generation, News - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $6.00 / 1,000 company records This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## 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 ## Startup Funding & Investor Intel > **TL;DR for VC/PE deal sourcing, B2B sales, and recruiters:** A Crunchbase-style funding feed rebuilt from PRIMARY sources - SEC Form D filings (the Regulation D exempt-offering notice almost every priced VC round files), EDGAR full-text search, and press coverage - not a Crunchbase scrape. Pull every fresh Form D in the last two weeks, look up a specific company's raise history, or map the companies a person sits on the board of. Each round comes parsed: issuer, offering amount, industry, the disclosed officers/directors/promoters, and any matching news story. Crunchbase killed its free API in 2025; this rebuilds its inputs from public, government-source data. Logged-out, public-data only. Free Apify plan covers exploration runs on your $5 platform credit. ### Run it in 30 seconds ```python ## Via the Apify Python SDK from apify_client import ApifyClient client = ApifyClient("") run = client.actor("seibs.co/startup-funding-intel").call(run_input={ "mode": "recent_rounds", "lookback_days": 14, "industry_groups": ["Technology"], "states": ["CA", "NY"], "user_agent_contact": "you@company.com" }) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) ```` Or via curl: ```bash curl -X POST "https://api.apify.com/v2/acts/seibs.co~startup-funding-intel/run-sync-get-dataset-items?token=" \ -H "Content-Type: application/json" \ -d '{"mode": "recent_rounds", "lookback_days": 14, "user_agent_contact": "you@company.com"}' ``` Or click "Try for free" on this page if you prefer the no-code UI. You must set a real `user_agent_contact` email - the SEC requires it. ### What you get Each run produces: - A clean dataset, filterable in the Apify console and downloadable as CSV or JSON - An OUTPUT.html dashboard preview of your top records - A sample-output preview at [`.actor/sample-output.json`](./.actor/sample-output.json) Three record types: - `funding_round_record` - one parsed Form D filing (issuer, offering amount, industry, exemptions, related persons, press) - `company_record` - a per-issuer rollup (total disclosed raised, round count, latest round) - `investor_graph_enrichment` - one searched person mapped to the companies they are a related person on, with co-investors ### Live example output Sample shapes are in [`.actor/sample-output.json`](./.actor/sample-output.json) (the same records demo mode pushes when inputs are missing). A live `recent_rounds` run over the last 14 days returns the newest Form D filings parsed into the schema above, one `funding_round_record` per filing and one `company_record` per distinct issuer, with press mentions attached where a recent news story matches the issuer name. ### What does Startup Funding Intel do? It treats SEC Form D as the primary-source funding feed it effectively is. When a startup closes a priced equity round under Regulation D, it files a Form D within 15 days disclosing the issuer, the offering amount (total / sold / remaining), the industry, the securities type, and the related persons (executive officers, directors, promoters). This actor: 1. **Finds** the filings - either all of them in a lookback window (`recent_rounds`), or the ones matching a company or person name via EDGAR full-text search. 2. **Parses** each `primary_doc.xml` defensively into a clean record - handling the real-world quirks (offering amounts reported as "Indefinite", first sales "yet to occur", multi-relationship people). 3. **Corroborates** with press - a Google News RSS lookup, fuzzy-matched to the issuer name, attaches recent funding stories. Press files *before* Form D, so a fresh mention confirms the round is real and recent. 4. **Resolves entities** with `rapidfuzz` so "Acme Robotics, Inc." in a filing, "Acme Robotics" in a headline, and the EDGAR display name link up - and weak matches are flagged with a `match_confidence` field rather than silently merged. ### Responsible use / data scope This actor is a **public-data tool** built on government open data. SEC EDGAR is public-by-law with no adverse platform owner - the safest class of source. It reads only logged-out, publicly-served endpoints (EDGAR full-text search, the EDGAR archives, Google News RSS) - no accounts, no cookies, no paywalls. It minimizes PII: it surfaces the issuer's disclosed related persons (a public-record field that the filer chose to put on a federal form) and firmographics; it never enriches into private contact data or resells personal contact lists. You are responsible for lawful use of the outputs (GDPR / CCPA apply to personal data even when public). This is the synthesis path - we rebuild Crunchbase's inputs from primary sources, we do not scrape Crunchbase. ### AI / RAG / Agent A turn-key funding feed for deal-sourcing AI, sales copilots, and recruiting bots. Records arrive pre-parsed with `total_offering_amount_usd`, `industry_group`, `filing_date`, `related_persons`, and `press_mentions`, so an agent can answer "which California tech companies filed a Form D over $10M this week, and which have press confirming a Series B?" without parsing XML. Compatible with **LangChain**, **LlamaIndex**, **Pinecone**, **Weaviate**, **Chroma**, and any **MCP**-aware agent runtime (a sibling `mcp-startup-funding-intel` actor is planned for direct tool-call wiring with agentic payments). ### Features - **Four modes** - recent-rounds firehose, per-company history, investor graph, and a scheduled watchlist monitor. - **Defensive Form D parser** - offering amounts (total / sold / remaining, with non-numeric "Indefinite" preserved), industry group, federal exemptions, date of first sale, issuer (name / CIK / state / incorporation year), entity type, related persons with normalized relationships, minimum investment, revenue range. - **Press corroboration** - up to 5 recent (180-day) news mentions per company from Google News RSS, fuzzy-matched to the issuer name. Soft-fail (press errors never abort the run). - **Entity resolution** - rapidfuzz `token_set_ratio` with documented accept / weak / reject thresholds; weak matches carry a `match_confidence` caveat. - **Investor graph** - companies a person is a related person on, co-investors seen on the same filings, total disclosed amounts, date range. - **SEC fair-access compliant** - required contact email in the User-Agent, <= 8 req/s throttle, retry/backoff on 429/503, and a browse-edgar fallback when full-text search is unavailable. - **Honest framing** - every round carries a `data_lag_note`; the investor graph carries a `graph_note` explaining Form D does not name LP/VC funds. - **Cost-control** - per-run budget guard + demo-mode soft-fail so runs finish SUCCEEDED. ### Use cases - **VC / PE deal sourcing** - a fresh Form D is an early signal of a closing round. Watch `recent_rounds` filtered to your thesis (industry + state + minimum amount). - **B2B sales triggers** - a fresh raise = budget. Route newly-funded companies to the AE who owns the territory. Pairs with the [b2b-sales-triggers](https://apify.com/seibs.co/b2b-sales-triggers) actor. - **Recruiting** - newly-funded scale-ups are hiring; combine with [hiring-signal-intel](https://apify.com/seibs.co/hiring-signal-intel) for the open-roles side. - **Investor relationship mapping** - `investor_search` shows which companies a person is a disclosed director/officer on and who they file alongside. - **Watchlist monitoring** - `funding_monitor` on a schedule alerts you when a target company files a new round. ### Modes | Mode | What it returns | |---|---| | `recent_rounds` | Every Form D / D/A filing in a lookback window (default 14 days), optionally filtered by industry group, state, and minimum offering amount. One `funding_round_record` per filing; one `company_record` per distinct issuer. | | `company_funding` | For each named company: its Form D history (resolved by name via EDGAR full-text search + fuzzy matching) plus press corroboration. Emits rounds + a company rollup. | | `investor_search` | For each named person: the Form D filings where they appear as a related person, rolled up into an `investor_graph_enrichment` (companies backed, co-investors, totals, date range). | | `funding_monitor` | A company watchlist intended for Apify Schedules. Monitor-mode delta digest of NEW rounds since the last run. | ### Input See [`.actor/input_schema.json`](./.actor/input_schema.json) for the full form. Key fields: ```json { "mode": "recent_rounds", "user_agent_contact": "you@company.com", "lookback_days": 14, "industry_groups": ["Technology", "Biotechnology"], "states": ["CA", "NY", "MA"], "min_offering_amount_usd": 1000000, "include_press": true } ``` For `company_funding` / `funding_monitor`, set `companies` (e.g. `["Acme Robotics", "Northwind AI"]`). For `investor_search`, set `investors` (e.g. `["Jane Smith"]`). The `user_agent_contact` email is required by the SEC and is intentionally not prefilled - a missing or placeholder value runs in demo mode instead of sending a fake identity to the SEC. ### Output One `company_record` per issuer (the headline rollup) followed by the `funding_round_record` rows, then any `investor_graph_enrichment` records. ```json { "record_type": "funding_round_record", "issuer_name": "Northwind AI, Inc.", "issuer_state": "CA", "form_type": "D", "is_amendment": false, "filing_date": "2026-05-22", "date_of_first_sale": "2026-05-15", "total_offering_amount_usd": 40000000.0, "amount_sold_usd": 40000000.0, "industry_group": "Technology", "federal_exemptions": ["06b", "3C"], "related_persons": [ {"name": "Maria Delgado", "relationship": "Executive Officer"}, {"name": "Priya Raman", "relationship": "Director"} ], "press_mentions": [ {"title": "Northwind AI raises $40M Series B led by Meridian Ventures", "source": "TechCrunch", "match_confidence": 97.0} ], "edgar_filing_url": "https://www.sec.gov/Archives/edgar/data/1999001/.../...-index.htm", "data_lag_note": "Form D often files days-to-weeks after the press announcement..." } ``` Filings that cannot be resolved or fetched still emit a `fetch_error` record with a human `reason` for a complete audit trail. ### Pricing Pay-per-event: | Event | Price | When charged | |---|---|---| | `company_record` | $0.006 | Per per-issuer rollup (total disclosed raised, round count, latest round). | | `funding_round_record` | $0.010 | Per parsed Form D filing returned (the base unit). | | `investor_graph_enrichment` | $0.012 | Per searched person rolled up into an investor graph. | | `scheduled_delta_run` | $0.050 | Once per scheduled monitor-mode run. | A run that returns nothing costs nothing. A typical `recent_rounds` run over 14 days that returns ~80 filings across ~60 issuers costs roughly $0.80 (rounds) + $0.36 (companies) = about $1.16. Narrow the lookback, industry, state, or minimum-amount filters to control volume. ### FAQ **Q: Why is a round missing?** A: Only Regulation D *exempt* offerings file Form D. Priced VC equity rounds (Series Seed/A/B...) almost always do, because they rely on the Rule 506(b)/506(c) exemption - so most venture rounds show up. But a round done under a different exemption (for example certain Reg A+ or Reg CF crowdfunding raises, or a fully registered offering) may not file a Form D, and so will not appear here. There is also a filing lag: the issuer has up to 15 days after the first sale to file, and amendments (D/A) follow later - so a round announced in the press today may not file for a week or two. That lag is exactly why this actor attaches press corroboration and stamps every record with a `data_lag_note`. **Q: Is this Crunchbase data?** A: No. This is the synthesis path - it rebuilds the *inputs* Crunchbase aggregates from public, government-source primary data (SEC Form D filings) plus public press, and never scrapes Crunchbase. Crunchbase killed its free API in 2025; rather than pay or scrape it, this actor goes to the source the filings come from. The trade-off is honest: Form D gives you the issuer, the offering size, the industry, the exemptions, and the disclosed officers/directors - but it does not name the venture funds or label the round "Series B" (the press mentions help fill that gap). It is a primary-source funding feed, not a re-sold commercial database. **Q: What does match\_confidence mean?** A: Linking the same company or person across SEC filings and news headlines is fuzzy - "Acme Robotics, Inc.", "Acme Robotics", and a padded headline like "Acme Robotics raises $40M" are the same entity, but a naive comparison would miss it. The actor uses `rapidfuzz` `token_set_ratio` (0-100) after normalizing the names (uppercasing, stripping punctuation and legal suffixes like Inc/LLC/Corp). A score of 90+ is accepted as a confident match with no caveat. A score of 75-89 is a *weak* match: the record is still returned, but it carries a `match_confidence` object with the score and a "verify before relying on it" note, so you decide rather than the actor silently merging two entities. Below 75 is treated as a different entity. Press headline matching uses a slightly lower floor plus a required funding-keyword filter to cut noise. **Q: Do I have to provide a contact email?** A: Yes. The SEC fair-access policy requires every automated request to identify itself with a real contact email or the IP gets banned. The actor sends it in the User-Agent header. It is intentionally not prefilled, because a placeholder would send a fake identity to the SEC - so a missing or `example.com` value runs in demo mode instead. **Q: Can I schedule this?** A: Yes. `funding_monitor` (or any mode under an Apify Schedule) gives you a hands-off feed. Pair it with monitor mode (below) so you only get the delta of new rounds. A daily `recent_rounds` over your thesis, or a weekly `funding_monitor` over a target-company watchlist, are the two common setups. ### Save your input as an Apify Task Apify Tasks let you save a configured input once and re-run it with one click - the foundation for schedules and monitor mode. 1. Click `Run` with your input configured (mode, contact email, filters). 2. Click `Save as task`. 3. Name it (e.g. `seed-stage CA tech - daily`). 4. Reload the task page and click `Start` anytime. ### Run this on a schedule with Apify Schedules 1. Save your input as a Task (above). 2. Go to https://console.apify.com/schedules and `Create new schedule`. 3. Pick your Task and set a cron expression (daily 8am: `0 8 * * *`; weekly Mondays 9am: `0 9 * * 1`). 4. Save. Each run surfaces the newest filings for your thesis or watchlist. ### Monitor mode When this actor runs under an Apify Schedule, or in `funding_monitor` mode, it emits a change digest of new rounds since the last run instead of repeating the full set, with a digest record at the top. Provide `monitor_webhook_url` and the digest also fires to your Slack channel. Cost: one `scheduled_delta_run` event ($0.05) per scheduled run plus standard PPE on the emitted records. ### Related Actors - [sec-edgar-intel](https://apify.com/seibs.co/sec-edgar-intel) - the broader SEC actor (8-K triggers, Form 4 insider trades, 13F positions, full-text search). This actor specializes its Form D leg into a funding feed. - [b2b-sales-triggers](https://apify.com/seibs.co/b2b-sales-triggers) - turn a fresh raise into an outbound sales trigger for your AE/SDR team. - [hiring-signal-intel](https://apify.com/seibs.co/hiring-signal-intel) - pair a raise with a hiring surge for a full "this company is scaling" picture. ### Support Open an issue via the Apify Store contact link. Include the run ID and input config so the issue is reproducible. ### Changelog See [CHANGELOG.md](./CHANGELOG.md). ### Found this useful? If this actor saved you time or money, please leave a quick review on the Apify Store. Reviews help other buyers find work that solves their problem: https://apify.com/seibs.co/startup-funding-intel#reviews # Actor input Schema ## `mode` (type: `string`): recent\_rounds = all Form D / D/A filings in a lookback window (optionally filtered by industry, state, min offering). company\_funding = named companies -> their Form D history + press corroboration. investor\_search = investor/person names -> Form D filings where they appear as related persons, rolled into an investor graph. funding\_monitor = a company watchlist for Apify Schedules (monitor-mode delta of NEW rounds since last run). ## `user_agent_contact` (type: `string`): A real contact email. The SEC fair-access policy requires every automated request to identify itself with a contact email or the IP gets banned. We send it in the User-Agent header. This is intentionally NOT prefilled - a placeholder would send a fake identity to the SEC, so a missing or example.com value triggers demo mode instead. Example: 'you@company.com'. ## `companies` (type: `array`): Company legal or common names to look up in Form D filings, e.g. \['Acme Robotics', 'Northwind AI']. The actor resolves each to an SEC issuer via full-text search and fuzzy name matching (rapidfuzz). Names that match weakly are still returned but carry a match\_confidence caveat. Hard cap of 50. ## `investors` (type: `array`): Investor or person names to search Form D 'related persons' for (executive officers, directors, promoters), e.g. \['Jane Smith', 'Reid Hoffman']. Builds an investor graph per name: companies backed, co-investors seen on the same filings, total disclosed amounts, date range. Form D does NOT name LP/VC funds, so this finds disclosed control persons, not fund investors. Hard cap of 25. ## `lookback_days` (type: `integer`): How far back to pull Form D filings in recent\_rounds mode. Default 14 (the last two weeks of fresh raises). Hard cap of 365. ## `industry_groups` (type: `array`): Keep only filings whose Form D industry group contains one of these (case-insensitive substring), e.g. \['Technology', 'Pooled Investment Fund', 'Biotechnology', 'Health Care']. Form D uses a fixed industry-group vocabulary. Leave empty for all. Hard cap of 15. ## `states` (type: `array`): Keep only filings whose issuer business state matches one of these 2-letter codes, e.g. \['CA', 'NY', 'TX', 'DE']. Leave empty for all states. Hard cap of 50. ## `min_offering_amount_usd` (type: `integer`): Keep only rounds whose disclosed total offering amount is at least this many dollars. Default 0 (no floor). Note: many Form D filings report 'Indefinite' (no numeric amount); when a floor > 0 is set, Indefinite-amount filings are excluded. ## `max_rounds` (type: `integer`): Hard cap on the number of Form D filings fetched and parsed in a run (recent\_rounds and per-name searches). Default 200. Hard cap of 1000. ## `include_press` (type: `boolean`): Attach up to 5 recent (within 180 days) press mentions per company from Google News RSS, fuzzy-matched to the company name. Press files BEFORE Form D, so a fresh mention corroborates the round. Press errors never kill the run (soft-fail). No extra charge. ## `monitor_webhook_url` (type: `string`): When this actor runs under an Apify Schedule (monitor mode) or in funding\_monitor mode, post the change digest of new rounds to this Slack-compatible webhook URL. ## `use_apify_proxy` (type: `boolean`): Route SEC and news requests through Apify Proxy. DATACENTER is sufficient - the SEC is a government source with a fair-access throttle, not anti-bot. ## `apify_proxy_groups` (type: `array`): Apify Proxy groups. DATACENTER is fine for SEC and Google News endpoints. ## `concurrency` (type: `integer`): Parallel SEC requests. The SEC fair-access ceiling is 10 req/sec; this is capped at 8 with polite spacing. Default 4. ## Actor input object example ```json { "mode": "recent_rounds", "user_agent_contact": "", "companies": [], "investors": [], "lookback_days": 14, "industry_groups": [], "states": [], "min_offering_amount_usd": 0, "max_rounds": 50, "include_press": true, "monitor_webhook_url": "", "use_apify_proxy": true, "apify_proxy_groups": [ "DATACENTER" ], "concurrency": 4 } ``` # Actor output Schema ## `datasetItems` (type: `string`): Narrow, token-efficient slice of every record. Consumer: LLM agents (Claude, GPT, LangChain tools), MCP hosts, deal-sourcing dashboards. ## `datasetItemsRounds` (type: `string`): All parsed Form D filings with full fields. Consumer: humans browsing, RAG ingest, CRM export, VC deal pipelines. ## `datasetItemsInvestors` (type: `string`): One row per searched investor/person: companies backed, co-investors, total disclosed, date range. Consumer: VC/PE relationship mapping, recruiting. ## `datasetItemsMcp` (type: `string`): First 50 overview records as a clean JSON array. Wrap on the agent side in an MCP tool-call envelope. Consumer: MCP servers, Claude Desktop, Cursor, OpenAI Assistants tool calls. ## `datasetItemsCsv` (type: `string`): Spreadsheet-friendly export of the overview view. Consumer: deal-sourcing teams, Excel / Google Sheets users. # 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 = { "mode": "recent_rounds", "lookback_days": 14, "max_rounds": 50 }; // Run the Actor and wait for it to finish const run = await client.actor("seibs.co/startup-funding-intel").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 = { "mode": "recent_rounds", "lookback_days": 14, "max_rounds": 50, } # Run the Actor and wait for it to finish run = client.actor("seibs.co/startup-funding-intel").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 '{ "mode": "recent_rounds", "lookback_days": 14, "max_rounds": 50 }' | apify call seibs.co/startup-funding-intel --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=seibs.co/startup-funding-intel", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Startup Funding & Investor Intel - Form D Rounds, Investors", "description": "Fresh startup funding rounds and investor intel synthesized from SEC Form D filings, EDGAR full-text search, and press coverage. A Crunchbase-style feed rebuilt from primary sources. For VC/PE deal sourcing, B2B sales (a fresh raise = budget), and recruiters. Public data only.", "version": "0.1", "x-build-id": "fCnaBaEGX6QBAaS4a" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/seibs.co~startup-funding-intel/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-seibs.co-startup-funding-intel", "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/seibs.co~startup-funding-intel/runs": { "post": { "operationId": "runs-sync-seibs.co-startup-funding-intel", "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/seibs.co~startup-funding-intel/run-sync": { "post": { "operationId": "run-sync-seibs.co-startup-funding-intel", "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": [ "mode", "user_agent_contact" ], "properties": { "mode": { "title": "Mode", "enum": [ "recent_rounds", "company_funding", "investor_search", "funding_monitor" ], "type": "string", "description": "recent_rounds = all Form D / D/A filings in a lookback window (optionally filtered by industry, state, min offering). company_funding = named companies -> their Form D history + press corroboration. investor_search = investor/person names -> Form D filings where they appear as related persons, rolled into an investor graph. funding_monitor = a company watchlist for Apify Schedules (monitor-mode delta of NEW rounds since last run).", "default": "recent_rounds" }, "user_agent_contact": { "title": "Contact email (REQUIRED - SEC fair-access)", "type": "string", "description": "A real contact email. The SEC fair-access policy requires every automated request to identify itself with a contact email or the IP gets banned. We send it in the User-Agent header. This is intentionally NOT prefilled - a placeholder would send a fake identity to the SEC, so a missing or example.com value triggers demo mode instead. Example: 'you@company.com'.", "default": "" }, "companies": { "title": "Companies (for company_funding / funding_monitor)", "maxItems": 50, "type": "array", "description": "Company legal or common names to look up in Form D filings, e.g. ['Acme Robotics', 'Northwind AI']. The actor resolves each to an SEC issuer via full-text search and fuzzy name matching (rapidfuzz). Names that match weakly are still returned but carry a match_confidence caveat. Hard cap of 50.", "default": [], "items": { "type": "string" } }, "investors": { "title": "Investors / people (for investor_search)", "maxItems": 25, "type": "array", "description": "Investor or person names to search Form D 'related persons' for (executive officers, directors, promoters), e.g. ['Jane Smith', 'Reid Hoffman']. Builds an investor graph per name: companies backed, co-investors seen on the same filings, total disclosed amounts, date range. Form D does NOT name LP/VC funds, so this finds disclosed control persons, not fund investors. Hard cap of 25.", "default": [], "items": { "type": "string" } }, "lookback_days": { "title": "Lookback window (days) for recent_rounds", "minimum": 1, "maximum": 365, "type": "integer", "description": "How far back to pull Form D filings in recent_rounds mode. Default 14 (the last two weeks of fresh raises). Hard cap of 365.", "default": 14 }, "industry_groups": { "title": "Industry-group filter (Form D categories)", "maxItems": 15, "type": "array", "description": "Keep only filings whose Form D industry group contains one of these (case-insensitive substring), e.g. ['Technology', 'Pooled Investment Fund', 'Biotechnology', 'Health Care']. Form D uses a fixed industry-group vocabulary. Leave empty for all. Hard cap of 15.", "default": [], "items": { "type": "string" } }, "states": { "title": "State filter (2-letter issuer state)", "maxItems": 50, "type": "array", "description": "Keep only filings whose issuer business state matches one of these 2-letter codes, e.g. ['CA', 'NY', 'TX', 'DE']. Leave empty for all states. Hard cap of 50.", "default": [], "items": { "type": "string" } }, "min_offering_amount_usd": { "title": "Minimum total offering amount (USD)", "minimum": 0, "maximum": 100000000000, "type": "integer", "description": "Keep only rounds whose disclosed total offering amount is at least this many dollars. Default 0 (no floor). Note: many Form D filings report 'Indefinite' (no numeric amount); when a floor > 0 is set, Indefinite-amount filings are excluded.", "default": 0 }, "max_rounds": { "title": "Max filings to process", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Hard cap on the number of Form D filings fetched and parsed in a run (recent_rounds and per-name searches). Default 200. Hard cap of 1000.", "default": 200 }, "include_press": { "title": "Include press corroboration", "type": "boolean", "description": "Attach up to 5 recent (within 180 days) press mentions per company from Google News RSS, fuzzy-matched to the company name. Press files BEFORE Form D, so a fresh mention corroborates the round. Press errors never kill the run (soft-fail). No extra charge.", "default": true }, "monitor_webhook_url": { "title": "Monitor webhook URL (Slack / email, optional)", "type": "string", "description": "When this actor runs under an Apify Schedule (monitor mode) or in funding_monitor mode, post the change digest of new rounds to this Slack-compatible webhook URL.", "default": "" }, "use_apify_proxy": { "title": "Use Apify Proxy", "type": "boolean", "description": "Route SEC and news requests through Apify Proxy. DATACENTER is sufficient - the SEC is a government source with a fair-access throttle, not anti-bot.", "default": true }, "apify_proxy_groups": { "title": "Proxy groups", "type": "array", "description": "Apify Proxy groups. DATACENTER is fine for SEC and Google News endpoints.", "default": [ "DATACENTER" ], "items": { "type": "string" } }, "concurrency": { "title": "Max concurrent SEC requests", "minimum": 1, "maximum": 8, "type": "integer", "description": "Parallel SEC requests. The SEC fair-access ceiling is 10 req/sec; this is capped at 8 with polite spacing. Default 4.", "default": 4 } } }, "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 } } } } } } } } } } ```