Why a YC Startup Database Matters to Your Cross-Border Operation
If you run an Amazon FBA business, a Shopify DTC brand, or a multi-marketplace operation, your biggest strategic advantage is not your ad spend or your supply chain—it’s your ability to see what’s coming before your competitors do. New tools, new logistics models, new payment rails, new advertising channels: they almost always appear first in the startup ecosystem, and almost always in the portfolios of top accelerators like Y Combinator and top VCs like a16z. The problem is that finding and monitoring those startups has been a manual, fragmented mess—bouncing between YC’s directory, a16z’s site, Crunchbase, LinkedIn, and a dozen browser tabs. ExploreYC just turned that mess into a single, open-source REST API covering 6,800+ YC and a16z companies, with cleaned data you can query, script, and build on. For cross-border operators, this isn’t a nice-to-have—it’s a competitive intelligence layer you can start using this week.
The Data Problem That Every Cross-Border Seller Knows Too Well
Your product research process probably looks like this: you spot a trend on TikTok Shop, run a Helium 10 product tracker, check Jungle Scout for historical sales data, and maybe glance at Google Trends. That works for fast-moving consumer goods. But when you’re looking for the next piece of infrastructure—a new fulfillment startup, a cross-border payment rail that might cut your FX costs by 2%, an AI tool that automates listing optimization for non-English markets—you’re stuck with the same manual grind that any startup investor faces. You open YC’s directory (if you even know how to navigate it), then a16z’s portfolio page, then start cross-referencing on Crunchbase, which requires a Pro subscription to see funding history. Then you search LinkedIn to find the founders. Then you check if the company is still alive or quietly dead.
That’s exactly the pain point Konstantin Borimechkov, the maker of ExploreYC, describes in his launch post: “I was prepping my YC application. I wanted to know: has anyone already done this idea? YC’s search gave me nothing useful. So I spent a weekend scraping their Algolia API, built a local database, ran embeddings against my pitch. and found 3 companies that had tried it.” (source). The same frustration applies to cross-border sellers trying to identify new tools or competitive threats. The data exists, but it’s scattered behind different interfaces, paywalls, and inconsistent schemas.
ExploreYC’s API solves this by offering a single endpoint (https://api.exploreyc.com/api/v1) where you can filter by VC source (yc, a16z, or all), batch, industry, country, hiring status, or full-text search. You can pull company details by ID or slug, including funding stage, IPO/M&A exits, acquirer, founders, and ticker. And it’s open source on GitHub, meaning you can fork it, extend it, or even run your own instance if you don’t trust the hosted version.
Why Amazon Sellers Should Care More Than Shopify Ones
Amazon’s ecosystem is notoriously opaque. You can’t easily query the status of every third-party tool that integrates with Seller Central. Yet many of the most valuable tools for Amazon sellers—inventory management, repricing, review monitoring, PPC automation—start as YC or a16z-backed startups. Think of Sellics (YC W15) or Jungle Scout (not YC, but many similar). If you could set up a query that alerts you when a new YC company is tagged with “e-commerce” and “Amazon,” you’d know about a potential competitor or partner months before the press release. Shopify sellers, by contrast, have a more transparent app store, but they still lack a systematic feed of emerging logistics and payment startups. An API that lets you filter by industry (“e-commerce,” “logistics,” “fintech”) and by funding stage can give you a lead on the next ShipBob or Stripe competitor before they hit scale.
What ExploreYC Actually Solves—and How It Differs from the Incumbents
The existing options for researching startup portfolios fall into three buckets, and none of them serve a cross-border seller well:
- Manual browsing: YC’s own directory and a16z’s portfolio page are free but have no API, no robust filtering, and no way to cross-reference between the two. You’re left clicking through company cards.
- Paid aggregators: Crunchbase, PitchBook, and CB Insights charge thousands per year for the kind of structured data ExploreYC gives away. And they often include noise from non-accelerator companies, making it harder to isolate top-tier signals.
- Scraped datasets: You can buy CSV dumps from aggregators on marketplaces like Scale, but they’re static and quickly stale.
ExploreYC sits in a fourth category: a free, open-source, regularly refreshed API that specifically targets YC and a16z—the two most relevant sources for early-stage e-commerce innovation. The maker claims data is “freshly polled every single day” (source) (see his reply to Henry Jung). That’s critical for cross-border sellers because startup status changes fast: a company that was “operating” a month ago may have shut down, pivoted, or been acquired. Knowing that a tool you were evaluating is dead saves weeks of wasted effort.
The web app that sits on top of the API adds a searchable interface with an interactive global map, AI research, funding analytics, and a live hiring board (1,400+ companies hiring). But for an operator, the API is the true unlock. You can pipe the data into a Slack bot, a Google Sheet via Apps Script, a custom dashboard in Metabase, or even a once-a-week email alert using Zapier (though Zapier doesn’t natively support custom REST APIs—you’d need Make or a quick Python script).
A Sidebar on Data Ethics and Scraping
The source reveals that ExploreYC’s YC data comes from scraping YC’s internal Algolia API, not from a documented public endpoint. Several commenters raise valid concerns about durability. One user asks: “since the ingestion pipeline hits YC’s internal Algolia endpoint rather than a documented public API, what’s your plan if YC changes that index’s config, adds auth, or just blocks the traffic pattern?” (source). The maker’s response is a mix of humor and realism: “plan is to have a fleet of contributors and ai agents that will figure the problem once it’s present :D jokes aside, web crawling has been a thing for decades now.” This is both honest and a risk you need to weigh. If you build a serious operational process around this API (e.g., weekly competitor monitoring), you need a fallback. The open-source nature helps: you can fork the project and add your own scraping logic if the upstream changes. But if you’re not technical, you’re trusting the maintainer’s cron job to keep running.
What Cross-Border Sellers Can Borrow: Building Your Own Competitive Intel Stack
The most valuable use case for this API is not “browse interesting startups”—it’s creating a systematic intelligence feed that surfaces e-commerce-specific signals. Here’s a concrete plan you could implement this week:
- Get a free API key in 30 seconds (the maker says non-expiring keys with per-key rate limits). Then run a curl command like the one in the launch post to test it:
curl -H "Authorization: Bearer YOUR_KEY" "https://api.exploreyc.com/api/v1?source=yc&industry=e-commerce&batch=W25"(assuming the API supports batch filters). The docs are interactive Swagger, so you can explore without writing code. - Set up a weekly cron job (or a simple scheduled script in Google Cloud Run or a $5 VPS) that queries for new companies in industries relevant to you: “e-commerce,” “logistics,” “payments,” “advertising,” “SaaS.” The API supports full-text search, so you can also search for keywords like “cross-border,” “fulfillment,” or “returns.”
- Pipe the results into a Telegram or Slack channel using a webhook. This gives you real-time alerts when a new startup that fits your criteria appears. For example, if you’re an Amazon seller in Europe, you might want to know about a new French fulfillment startup before your competitors do.
- Use the batch “Wrapped” analytics to understand trends. The maker mentions “Batch ‘Wrapped’ shareables”—these are likely aggregated stats for a given YC batch. You can see which industries are getting funded and at what stages, helping you decide where to invest your own product development or partnership efforts.
A user review on Product Hunt illustrates the power of this approach: “Ran a search for a rough idea I’ve been noodling on and the validator actually surfaced two YC companies from different batches that tried something adjacent - one pivoted, one shut down. That’s a completely different kind of signal than the usual ‘sounds promising!’ you get from just asking an AI chatbot.” (source). Replace “rough idea” with “new product category” and you’ve got a way to avoid building something that’s already been proven unviable.
Where the Math Breaks: Data Freshness, Entity Resolution, and Upstream Dependency
I want to be honest about the limitations, because overselling this API would be doing you a disservice. Three issues stand out:
1. Entity resolution across YC and a16z. A commenter named Dipankar Sarkar asked the exact right question: “When YC and a16z conflict on a field, is there a documented precedence?” (source). The maker didn’t answer that specific question, which suggests the canonical ID mapping might not be robust. If you’re building a tool that relies on accurate funding stage or founder data, you’ll need to test the merging logic yourself. The open-source nature lets you inspect the code, but it also means you’re responsible for verifying.
2. Reliance on YC’s Algolia endpoint. While daily scraping is admirable, it’s fragile. If YC adds rate limits or changes their front-end API, the pipeline breaks. The maker’s response about “multiple ways to overcome” is not a guarantee. For a low-stakes alert system, that’s fine. For a production dependency that your inventory forecasting or partnership decisions rely on, you’d want a fallback like Crunchbase’s API (paid) or manual verification.
3. Historical re-tagging and category drift. Another user questioned how YC’s category definitions evolve over time—e.g., what counted as “AI” in 2020 vs. 2025. The maker didn’t address whether old data is re-tagged or frozen. If you’re analyzing multi-year trends, inconsistent categorization could mislead you into thinking a category is growing when it’s just being redefined.
What I’d Watch / Test Next
For cross-border sellers, I’d recommend two concrete actions this week:
Sign up for an API key and run a search for all YC batches in the last 3 years filtered by industry “e-commerce” or keyword “marketplace.” Export the results into a Google Sheet. Then cross-reference each company against Crunchbase or just a manual Google search to verify the status. This will give you a baseline sense of data accuracy. If you find more than 10% of companies are mislabeled or dead, reconsider relying on the API for decision-making.
Build a simple automation that sends you a weekly email of new companies. Since the API is RESTful, you can use Make (formerly Integromat) to schedule a GET request and parse the JSON into an email. Or, if you’re comfortable with Python, a 20-line script running on PythonAnywhere can do the same for free. The goal is to stop searching for tools manually and instead let the data come to you.
The real opportunity here isn’t the web app—it’s the API plus open-source ethos. If the community grows, this dataset could become the canonical, free source for YC and a16z intelligence. For a cross-border operator, that means you can stop paying for Crunchbase Pro and instead invest that $300/month into actual product testing. But don’t blindly trust it. Fork the repo, run your own scrapers if you can, and treat the API as a starting point—not a truth database. The edge goes to those who automate the research, not those who do the research.
