Overview
An emerging venture capital fund uses Anysite’s API to power a fully automated deal sourcing pipeline — discovering companies, researching founders, and acquiring contact information at a fraction of the cost of traditional VC intelligence platforms. Built entirely with a no-code platform, the pipeline processes ~85 API calls per day without requiring an engineering team.
At **0.06percontactacquired∗∗anda∗∗73.528,000/year enterprise tooling with a $30/month Anysite subscription — proving that emerging funds can build institutional-grade deal sourcing infrastructure on a bootstrapped budget.
The Challenge: Deal Sourcing Is Broken for Emerging Funds
Venture capital is fundamentally a deal flow business. The best returns go to funds that find promising companies before the market catches on — and that means systematically discovering founders, not waiting for warm introductions.
But the tools designed for deal sourcing are built for large, established funds:
- PitchBook starts at ~$28,000/year — prohibitive for solo GPs and emerging fund managers
- Crunchbase Pro and Dealroom offer company databases but limited founder contact data
- Manual research — trawling LinkedIn, AngelList, and news sites — doesn’t scale beyond a handful of deals per week
For a small or emerging fund, the math doesn’t work. You need institutional-quality deal flow without institutional budgets. And you need it automated, because a solo GP or small team can’t spend hours each day on manual prospecting.
The Solution: A No-Code Pipeline on Anysite
This fund took a different approach. Instead of subscribing to expensive VC intelligence platforms, they built their own deal sourcing pipeline using Anysite’s API as the data layer and a no-code platform for the workflow logic.
The result: a 4-stage automated pipeline that runs daily, continuously discovering companies and founders in target sectors — without writing a single line of code.
The Workflow
The pipeline follows a logical progression from company discovery to founder contact:
Stage 1: Company Discovery (~25% of API usage)
The pipeline starts by searching for companies matching the fund’s investment thesis — by industry, size, keywords, and growth signals.
/linkedin/search/companies — Find companies by sector, size, and keywords/linkedin/search/jobs — Open positions as growth signals (a startup hiring aggressively is likely scaling)
Stage 2: Company Research (~25% of API usage)
For each discovered company, the pipeline pulls detailed profiles to assess fit:
/linkedin/company — Full company profile: industry, employee count, specialties, headquarters/google/company — Cross-referenced data from Google and the open web
This dual-source approach ensures the fund has a complete picture — LinkedIn for professional data, Google for broader context like funding announcements and press coverage.
Stage 3: Founder Discovery (~25% of API usage)
Once a company passes the research filter, the pipeline identifies founders and key executives:
/linkedin/company/employees — List all employees at the target company/linkedin/user — Full profiles for founders and C-suite executives/linkedin/search/users — Find specific roles (CEO, CTO, Co-founder) at the company
For qualified founders, the pipeline acquires contact information for direct outreach:
/linkedin/user/email — Email lookup for founders and decision-makers
The 73.5% profile-to-email conversion rate means that nearly three out of four researched founders yield actionable contact data — a remarkably efficient pipeline output.
Results & Metrics
| Metric | Value |
|---|
| Total API calls (Q1 2026) | 7,663 |
| Daily average | ~85 calls/day |
| Endpoint distribution | Balanced ~25% across all 4 stages |
| Cost per contact acquired | $0.06 |
| Profile-to-email conversion | 73.5% |
| Anysite plan cost | $30/month (MCP Unlimited) |
| Replaced tooling cost | ~$28,000/year (PitchBook equivalent) |
| Engineering team required | None (no-code build) |
The Cost Equation
The economics are compelling:
- Anysite: 30/month=360/year for data access at API level
- PitchBook: ~$28,000/year for a comparable (but different) deal intelligence platform
- Cost difference: 78x cheaper for the data layer
This is not an apples-to-apples comparison — PitchBook offers financial data, deal history, and a full UI that Anysite doesn’t provide. The point is that for the specific capability this fund needed (company discovery + founder profiles + contact data), Anysite delivers at a fraction of the cost.
Key Anysite Endpoints Used
| Endpoint | Pipeline Stage | Purpose |
|---|
/linkedin/search/companies | Company Discovery | Find companies by sector, size, keywords |
/linkedin/search/jobs | Company Discovery | Hiring activity as growth signal |
/linkedin/company | Company Research | Full company profile and firmographics |
/google/company | Company Research | Cross-referenced web data |
/linkedin/company/employees | Founder Discovery | Map employees at target companies |
/linkedin/user | Founder Discovery | Full founder/executive profiles |
/linkedin/search/users | Founder Discovery | Find specific roles at companies |
/linkedin/user/email | Contact Acquisition | Email lookup for outreach |
Key Takeaways
- No-code is production-ready. A VC fund built a fully automated deal sourcing pipeline without writing code — the combination of Anysite’s API and a no-code workflow platform is sufficient for production use.
- Emerging funds can compete on deal flow. At $30/month, institutional-grade founder discovery is accessible to solo GPs, angel investors, and emerging fund managers who were previously priced out of VC intelligence tools.
- Balanced pipelines are efficient pipelines. The ~25% distribution across all four stages shows a pipeline with no bottlenecks — every stage contributes equally to the output.
- 73.5% conversion proves data quality. Nearly three-quarters of researched founders yield actionable contact data, validating Anysite’s LinkedIn data coverage for VC deal sourcing use cases.
