Documentation Index
Fetch the complete documentation index at: https://buildingfor.vc/llms.txt
Use this file to discover all available pages before exploring further.
Overview
What data you need depends on your fund: stage focus, sector specialization, team size, and budget. A pre-seed fund sourcing emerging founders needs different data than a growth fund doing due diligence on Series B companies.
This page outlines starter kits for different fund profiles. These are starting points, not prescriptions. Your specific needs will vary.
Pre-Seed / Seed Focus
You’re looking for companies before anyone else knows about them. Signal data based on government registries matters more than comprehensive funding history, though even if you have a comprehensive funding database, you may not find all the companies you’re interested in.
What you need:
- Data to support your macro and market trend research
- Early-stage signal data (who’s starting companies, what’s trending)
- Founder and team data (background, previous experience)
- Basic company data (to track what you find)
What you probably don’t need yet:
- Comprehensive funding databases (most of your targets won’t be in them)
- Detailed financial data (too early for meaningful financials)
Typical stack:
| Category | Recommendation |
|---|
| Early Signal data | Gravity (US) or Evertrace (Europe) |
| People and Company data | Choose either People Data Labs or Coresignal for coverage of people and companies |
| Research tools | Perplexity API for quick market research |
Series A / Series B Focus
You’re evaluating companies with some traction. Need a balance of signal data and comprehensive coverage.
What you need:
- Funding history and investor data
- Growth signals (hiring, web traffic, product launches)
- Team composition and changes
- Competitive landscape data
What you probably don’t need:
- Deep public market data
- Heavy patent/research databases (unless sector-specific)
Typical stack:
| Category | Recommendation |
|---|
| Company data | Crunchbase or Dealroom, if you can splurge: PitchBook |
| Signal data | Specter or Harmonic for growth signals |
| People data | People Data Labs, Coresignal, or MixRank for team composition |
| Web traffic | SimilarWeb if evaluating consumer companies |
| Research | Perplexity API or Exa for competitive research |
Growth / Late Stage Focus
You’re doing deeper due diligence on established companies. Comprehensive data and financial metrics matter most.
What you need:
- Comprehensive funding databases
- Financial and operational metrics
- Market and competitive analysis
- Public company comparables
What you probably don’t need:
- Early-stage signal data (your targets are already known)
Typical stack:
| Category | Recommendation |
|---|
| Company data | PitchBook for comprehensive financials, valuations, cap tables |
| Financial data | S&P Capital IQ for public comps |
| People data | People Data Labs for team composition and hiring trends |
Deep Tech / Bio Focus
You’re evaluating technical founders and novel technology. Research and patent data become critical.
What you need:
- Academic publication databases
- Patent and IP data
- Technical founder backgrounds
- Research institution connections
Additional considerations:
- Many deep tech companies won’t appear in standard funding databases until later
- Founder evaluation requires different signals (publications, citations, lab affiliations)
Typical stack:
| Category | Recommendation |
|---|
| Academic | arXiv (AI/ML, physics), PubMed (bio/healthcare) |
| Research tools | Semantic Scholar for citation networks and research impact or Lens for linking patents to academic research |
| People data | People Data Labs for founder backgrounds |
| Category | Recommendation |
|---|
| Clinical trials | ClinicalTrials.gov |
| Drug pipeline | BioMedTracker for pipeline intelligence |
| FDA data | FDA databases |
Regional / Sector Specialist
You focus on a specific geography or vertical. Niche data providers often have better coverage than generalists.
What you need:
- Regional/sector-specific data providers
- Local market intelligence
- Sector-specific signals and metrics
Key insight:
Generalist data providers often have weak coverage outside US tech. If you invest in Europe, Asia, or specific verticals, look for specialized providers who focus on your market.
By geography:
| Region | Recommendations |
|---|
| US | Gravity for signals, Crunchbase for company data |
| Europe | Evertrace for signals, Dealroom for company data |
| Sector | Recommendations |
|---|
| Consumer | SimilarWeb for web traffic, data.ai for mobile apps |
| E-commerce | Jungle Scout for Amazon, SimilarWeb for traffic |
| Real estate | CARTO or SafeGraph for location intelligence |
| Fintech | SEC EDGAR for filings, standard company providers for funding data |
| Climate | EIA for energy data, EPA databases for emissions |
Budget Considerations
Your data budget should scale with fund size and strategy:
- Small fund (under $50M): Focus on 1-2 core providers. Start with what you absolutely need.
- Mid-size fund ($50-250M): Can afford broader coverage. 3-5 providers typical.
- Large fund (over $250M): 3-5 providers (but typically more expensive), then additional budget reserved for project or deal specific data sources.
