# Sequoia Capital Portfolio Scraper (`nexgendata/sequoia-portfolio-scraper`) Actor The only structured Sequoia + Peak XV portfolio feed (~710 companies). - **URL**: https://apify.com/nexgendata/sequoia-portfolio-scraper.md - **Developed by:** [Stephan Corbeil](https://apify.com/nexgendata) (community) - **Categories:** Business, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $750.00 / 1,000 portfolio companies 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 ## Sequoia Capital Portfolio Scraper **The only structured feed of the full Sequoia + Peak XV portfolio.** Returns ~710 companies across Sequoia Capital (US, ~406) and Peak XV Partners (former Sequoia India / Southeast Asia, ~304). One dataset row per portfolio company, with the fields VC sourcing analysts actually look up: **sector, partnered year, founded year, current status (Active / Acquired / Public), partner name, founders, website, twitter, linkedin, geography**. ### Why this exists (and why no one else has it) Sequoia's public site at https://www.sequoiacap.com/our-companies/ shows **only ~52 curated highlights** out of a 400+ company portfolio. Same on Peak XV. There is **no public portfolio export** — no CSV, no API, no downloadable list. This scraper consumes the canonical XML sitemap (`/company-sitemap.xml`) that Sequoia uses to feed search engines, then visits each `/companies/{slug}/` detail page in parallel. Result: a clean, structured, complete portfolio you can import into a CRM, an outbound sourcing pipeline, or a CB Insights / PitchBook replacement. **Premium positioning:** $0.75 per company. That is roughly 5–10× the entry-tier VC scrapers because (a) Sequoia is a top-three brand, (b) data scarcity is real, (c) the analyst on the buyer side earns this price back the first time they don't pay a $5K/seat database subscription for the same lookup. ### What you get Per portfolio company: - `name` — company name - `slug` — URL-safe identifier (matches the Sequoia detail page slug) - `url` — Sequoia / Peak XV detail page URL - `description` — company one-liner - `sector` / `sectors[]` — Sequoia's own sector taxonomy (Consumer, Enterprise, Healthcare, Financial Services, GTM, Bio, Crypto, AI, Infrastructure, FinTech, HealthTech, EdTech, D2C, etc.) - `founded_year` — year the company was founded - `partnered_year` / `year_invested` — year Sequoia first invested - `acquired_year` — year of acquisition (if exited) - `ipo_year` — year listed publicly (if IPO'd) - `status` — derived label: `Active (Private)` / `Acquired (YYYY)` / `Public/IPO (YYYY)` - `partner` / `partners[]` — Sequoia investment partner(s) on the deal (Bryan Schreier, Andrew Reed, Jim Goetz, Shailendra Singh, etc.) - `founders[]` — founder names (when surfaced on the detail page) - `website` — company website - `twitter_url`, `linkedin_url` — official social profiles - `geography` — US (Sequoia Capital), India, SEA, or India/SEA (Peak XV) - `source_firm` — `Sequoia Capital` or `Peak XV (Sequoia India/SEA)` - `source_sitemap_lastmod` — when Sequoia last updated this company's page - `scraped_at` — UTC ISO timestamp of this run ### Input | Field | Type | Description | |------|------|-------------| | `geographyFilter` | enum | `Global` (default) / `US` / `India` / `SEA`. Picks which sitemap to crawl. | | `sectorFilter` | string[] | Optional substring filter on sector pills (e.g. `["FinTech", "AI"]`). | | `stageFilter` | string[] | Optional substring filter on derived status (e.g. `["Acquired"]` for M&A leads, `["Public"]` for IPOs). | | `yearFromTo` | object | Inclusive bounds on `partnered_year`, e.g. `{"from": 2020, "to": 2026}` for recent vintage. | | `maxResults` | integer | Cap on dataset rows (1–1000, default 100). | ### Use cases - **VC sourcing & competitive intel.** Pull the full Sequoia + Peak XV roster, dedupe against your CRM, find overlap with YC, a16z, Founders Fund, Bessemer, Greylock, Lightspeed. - **M&A target lists.** Filter `stageFilter=["Acquired"]` to study Sequoia's exit playbook, or `stageFilter=["Active"]` with a vintage window to find growth-stage targets approaching their exit window. - **Founder enrichment.** Cross-reference `founders[]` and `partners[]` with LinkedIn / Crunchbase enrichment actors to build a deal-team map. - **BD prospecting.** Sequoia-backed companies are pre-qualified buyers for many enterprise SaaS categories. Filter by sector, send a sequence. - **Market mapping.** Group by `sector` + `partnered_year` to see where Sequoia leaned in each vintage. ### Companion actors - **YC Companies Directory** — Y Combinator alumni; large overlap with Sequoia's early-stage portfolio (Stripe, Airbnb, DoorDash were both YC and Sequoia). - **a16z Portfolio Scraper** — direct competitor portfolio for cross-firm comparison. - **Startup Funding Tracker** — recent rounds + valuations to enrich Sequoia-backed companies. - **500 Global Companies Directory** — accelerator alumni at the early-stage entry point. Combine any of these to build the most complete sourcing pipeline on the market. ### Pricing Pay-per-event: - **Per company** — $0.75 (primary event, charged on every dataset row) - **Actor start** — $0.00005 (negligible) You only pay for the rows you actually receive. Filtering by sector / status / year does not cost extra. ### Technical notes - Static HTML parsing. No JS rendering, no headless browser. - Apify residential proxy used by default for IP rotation. - Concurrent fetch (8-way) — full Global crawl (~710 companies) completes in ~3–5 minutes. - Detail-page selectors handle both the Sequoia `clist__item` markup and the Peak XV `company__milestone` markup. - Robust to either site reordering the milestones / partners / categories blocks. ### Limitations - **Sequoia China (HongShan)** is **not** in scope. Sequoia US, Sequoia China, and Peak XV (India/SEA) split into three independent firms in 2023; HongShan runs separate infrastructure that does not expose a comparable public sitemap. This actor covers Sequoia US + Peak XV only. - The original **stage-invested label** (Series A vs B vs C at time of investment) is **not surfaced** on Sequoia detail pages and therefore not in the output. We expose `partnered_year` (first-investment year) and `status` (current state) instead — sufficient for almost all sourcing use cases. - For companies that have **been acquired but later acqui-spun-back-out**, the `acquired_year` reflects what Sequoia shows on the page, which may lag real-world events by 0–6 months. # Actor input Schema ## `geographyFilter` (type: `string`): Which Sequoia portfolio to scrape. 'US' = Sequoia Capital (sequoiacap.com, ~406 companies). 'India' or 'SEA' = Peak XV Partners, the former Sequoia India/SEA (peakxv.com, ~304 companies — Practo, Freshworks, Zomato, Druva, BYJU'S, Razorpay, etc.). 'Global' = both lists merged (~710 companies). Note: Sequoia China (HongShan) is not covered — they run separate infrastructure. ## `sectorFilter` (type: `array`): Restrict to portfolio companies whose Sequoia sector pill matches any of these strings (case-insensitive substring). Common Sequoia sector tags: 'Consumer', 'Enterprise', 'Financial Services', 'Healthcare', 'GTM' (Go-To-Market), 'Bio', 'Crypto', 'AI', 'Infrastructure', 'Apps', 'Data', 'Climate'. Peak XV adds 'FinTech', 'HealthTech', 'EdTech', 'D2C', 'SaaS', 'AI'. Empty = no sector filter. ## `stageFilter` (type: `array`): Restrict by current company status (case-insensitive substring match against derived status string). Useful values: 'Active' (still private), 'Acquired' (M&A exit), 'Public' or 'IPO' (listed). Sequoia detail pages do not surface the original stage-invested label explicitly, so this filter operates on the derived current status rather than the historical Series A/B/C label. Empty = ALL statuses. ## `yearFromTo` (type: `object`): Restrict to portfolio companies whose 'Partnered' year (year of first Sequoia investment) falls within this inclusive range. Sequoia's portfolio spans 1972 (Atari) through present. Examples: from=2020, to=2026 for recent vintage; from=2010, to=2015 for the unicorn-era cohort. Either bound may be omitted. ## `maxResults` (type: `integer`): Maximum number of portfolio companies to return (1–1000). Each company is one dataset row. The full combined catalog currently holds ~710 entries (406 Sequoia US + 304 Peak XV India/SEA). ## Actor input object example ```json { "geographyFilter": "Global", "sectorFilter": [], "stageFilter": [], "yearFromTo": { "from": null, "to": null }, "maxResults": 100 } ```` # 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 = { "geographyFilter": "Global", "sectorFilter": [], "stageFilter": [], "yearFromTo": { "from": null, "to": null }, "maxResults": 100 }; // Run the Actor and wait for it to finish const run = await client.actor("nexgendata/sequoia-portfolio-scraper").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 = { "geographyFilter": "Global", "sectorFilter": [], "stageFilter": [], "yearFromTo": { "from": None, "to": None, }, "maxResults": 100, } # Run the Actor and wait for it to finish run = client.actor("nexgendata/sequoia-portfolio-scraper").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 '{ "geographyFilter": "Global", "sectorFilter": [], "stageFilter": [], "yearFromTo": { "from": null, "to": null }, "maxResults": 100 }' | apify call nexgendata/sequoia-portfolio-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nexgendata/sequoia-portfolio-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Sequoia Capital Portfolio Scraper", "description": "The only structured Sequoia + Peak XV portfolio feed (~710 companies).", "version": "0.0", "x-build-id": "euRBodxQ2pL80T2Bw" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nexgendata~sequoia-portfolio-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nexgendata-sequoia-portfolio-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nexgendata~sequoia-portfolio-scraper/runs": { "post": { "operationId": "runs-sync-nexgendata-sequoia-portfolio-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nexgendata~sequoia-portfolio-scraper/run-sync": { "post": { "operationId": "run-sync-nexgendata-sequoia-portfolio-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "geographyFilter": { "title": "Geography", "enum": [ "Global", "US", "India", "SEA" ], "type": "string", "description": "Which Sequoia portfolio to scrape. 'US' = Sequoia Capital (sequoiacap.com, ~406 companies). 'India' or 'SEA' = Peak XV Partners, the former Sequoia India/SEA (peakxv.com, ~304 companies — Practo, Freshworks, Zomato, Druva, BYJU'S, Razorpay, etc.). 'Global' = both lists merged (~710 companies). Note: Sequoia China (HongShan) is not covered — they run separate infrastructure.", "default": "Global" }, "sectorFilter": { "title": "Sector / category filter (optional)", "type": "array", "description": "Restrict to portfolio companies whose Sequoia sector pill matches any of these strings (case-insensitive substring). Common Sequoia sector tags: 'Consumer', 'Enterprise', 'Financial Services', 'Healthcare', 'GTM' (Go-To-Market), 'Bio', 'Crypto', 'AI', 'Infrastructure', 'Apps', 'Data', 'Climate'. Peak XV adds 'FinTech', 'HealthTech', 'EdTech', 'D2C', 'SaaS', 'AI'. Empty = no sector filter.", "items": { "type": "string" } }, "stageFilter": { "title": "Status filter (optional)", "type": "array", "description": "Restrict by current company status (case-insensitive substring match against derived status string). Useful values: 'Active' (still private), 'Acquired' (M&A exit), 'Public' or 'IPO' (listed). Sequoia detail pages do not surface the original stage-invested label explicitly, so this filter operates on the derived current status rather than the historical Series A/B/C label. Empty = ALL statuses.", "items": { "type": "string" } }, "yearFromTo": { "title": "Year invested range (optional)", "type": "object", "description": "Restrict to portfolio companies whose 'Partnered' year (year of first Sequoia investment) falls within this inclusive range. Sequoia's portfolio spans 1972 (Atari) through present. Examples: from=2020, to=2026 for recent vintage; from=2010, to=2015 for the unicorn-era cohort. Either bound may be omitted." }, "maxResults": { "title": "Max companies", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of portfolio companies to return (1–1000). Each company is one dataset row. The full combined catalog currently holds ~710 entries (406 Sequoia US + 304 Peak XV India/SEA).", "default": 100 } } }, "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 } } } } } } } } } } ```