Great, Differentiated Diligence from Public Data
Traditional venture due diligence relies on a simple assumption: you get access to the right information to make a decision. You review pitch decks, financial projections, customer references. You talk to the founders, the board, maybe some customers.
But that information is curated. It's designed to convince you. And for early-stage companies, that information often doesn't exist yet.
What if you could assess company health without relying on any of that? Using only publicly available signals that founders can't control?
Three Case Studies: Same Tool, Three Different Insights
The following case studies come from real investment analysis reports generated by DiligenceAI, an alternative data-based fundamental research tool that analyzes product-market fit, market trends, and founder strength using public data sources. Despite having no access to private financial information for two of these companies, the tool produced differentiated insights across all company stages.
Case 1: Deel
$12 billion valuation • Established HR SaaS
Investment Score: 80/100 • Recommendation: INVEST • Confidence: 85%
Deel is a multi-billion dollar company. We don't have access to their ARR, their NRR, their churn rate, or any of their private metrics. So how do we evaluate it?
Market Signals We Found:
- →Top Google search rankings for core keywords ('Deel | Global Payroll, Compliance, HR Solutions') signal strong organic discoverability
- →Google search interest trend: increasing — people are searching for Deel more frequently
- →YouTube channel: 386 videos, 337M+ total views — consistent content creation at scale
- →YouTube growth trend: increasing with growing subscriber base (9,750+) — the content strategy is working
The insight: None of these signals are self-fulfilling prophecies. Deel can't artificially inflate Google search volume or YouTube views. The market is genuinely interested in their solution. This validates that their product-market fit is real and accelerating—without us ever seeing a single financial number.
Case 2: Relay.app
Fast-growing pre-Series A • AI Automation Platform
Investment Score: 60/100 • Recommendation: MAYBE • Confidence: 65%
Relay.app looks great on the surface. Strong Product Hunt reception. Founder with Google background and successful exits. Growing search interest. Positive user testimonials.
But one metric tells a different story.
The Signal That Matters:
YouTube channel growth trend: DECREASING
Despite a reasonable subscriber base and existing videos, the growth is slowing. YouTube engagement is a leading indicator of momentum. If people are watching fewer videos from your channel, they're losing interest in your product.
This doesn't mean Relay.app will fail. It means the early momentum is cooling. The Product Hunt launch was strong, but the sustained engagement and organic interest are declining. This is a yellow flag that contradicts the initial positive signals.
The insight: Early signals (Product Hunt) are useful, but they're not predictive of sustained success. YouTube trends, search trends, and ongoing engagement metrics reveal whether initial momentum is converting into real, sustained product-market fit. Relay.app needs to prove it can reverse this trend.
Case 3: Content Hurricane
Pre-revenue • AI Content Creation Tool
Investment Score: 55/100 • Recommendation: PASS • Confidence: 65%
Content Hurricane makes bold claims. Their pitch deck promises 277% SEO improvement and 99.8% cost reduction. On paper, if true, this would be a game-changer for content creation.
But here's what the alternative data reveals:
What The Market Signals Show:
- →Limited independent user reviews or testimonials — despite marketing efforts, early-stage external validation is minimal
- →Sparse organic community mentions — Reddit, forums, and other platforms show light discussion relative to marketing volume
- →Non-technical founder leading AI product — suggests reliance on technical partners or contractors rather than in-house capability
- →Limited public proof points — few published case studies or before/afters from real users yet
The pitch deck claims are ambitious. What's notable is that the market hasn't yet generated the kind of organic validation signals—independent reviews, community discussion, user testimonials—that would support those claims. This is typical for very early-stage products, but it also means the claimed results haven't been independently verified by the market yet.
The insight: The tool works regardless of stage or outcome. For early-stage products, the absence of market validation signals isn't necessarily damning—it's expected. But it does mean there's a gap between pitch claims and demonstrated market reality. Only time will tell whether that gap closes.
The Pattern: Alternative Data Works Across All Stages
These three companies span completely different stages: Deel (established market leader), Relay.app (growth-stage), and Content Hurricane (pre-revenue). Yet the same methodology—analyzing public market signals—provided differentiated insights for all three.
Deel
Validated a mature company without access to private financials
Relay.app
Identified momentum decline despite strong early signals
Content Hurricane
Revealed gap between pitch claims and current market validation for early-stage product
For Deel, we couldn't access ARR or NRR. For Relay.app, we don't know their MRR or churn rate. For Content Hurricane, there's no revenue data at all. Yet in all three cases, alternative data sources (Google trends, YouTube metrics, Reddit discussions, founder credibility, product reviews) gave us a clear picture of market reality.
Where Does This Alternative Data Come From?
Google Search Trends
Search volume and interest trends reveal market demand and awareness. More searches = more market interest. Increasing trends = accelerating demand.
YouTube Channel Metrics
Video view counts, subscriber growth, and content frequency reveal audience engagement. Channel growth trends are leading indicators of product momentum.
Product Hunt & Community Reception
Initial launch performance shows how the early adopter community receives the product. High engagement is a positive signal, but not predictive of sustained success.
Reddit & Forum Discussions
Organic user discussions reveal authentic feedback. Real problems and real solutions generate real conversation. Their absence is a red flag.
Social Media & Public Profiles
Founder credibility, public reputation, and professional background reveal execution capability. A non-technical founder leading an AI product is concerning.
Customer Reviews & Testimonials
Public reviews (or their absence) reveal product quality. A product with no independent testimonials, despite marketing efforts, likely isn't delivering results.
Why This Matters For Venture Investors
1. Democratized Due Diligence
You don't need special access or insider information. Public market signals are available to everyone. This levels the playing field against mega-funds with extensive data subscriptions.
2. Early Stage Advantage
For pre-revenue and early-stage companies, traditional financial metrics don't exist. Alternative data fills that gap, revealing market validation (or lack thereof) long before ARR or NRR become relevant.
3. Founder Reality Check
Pitch decks and founder stories can be compelling. But market data reveals whether the narrative matches reality. Bold claims without supporting evidence are warnings.
4. Momentum Detection
YouTube trends, search trends, and community sentiment are leading indicators. You can often detect momentum decline before it shows up in financial metrics.
5. Cross-Stage Applicability
The same methodology works for pre-revenue startups, growth-stage companies, and mature market leaders. One framework, full spectrum coverage.
The Bottom Line
Pitch claims are cheap. Market signals are real. A company with genuine product-market fit creates an organic trail of evidence: search volume increases, YouTube viewership grows, users discuss it online, reviews accumulate, and momentum accelerates. This happens because the product is solving real problems, not because the marketing department decided it should.
Conversely, a product without market validation—despite bold claims—reveals itself through the absence of these signals. No reviews. No community discussion. Declining engagement. Founder capability mismatches. These aren't speculative red flags; they're data.
By analyzing alternative data sources, you gain an edge that traditional due diligence can't provide. You see beyond the pitch. You validate across all company stages. And you spot momentum shifts before others do.
The market reveals truth. You just need to know where to look.