How and why venture capital due diligence is evolving

Venture capital has always been about making big, high-conviction bets in uncertain environments. But now, the stakes–and the uncertainty–are higher than ever before. 

There’s a shakeup underway across VC, at the convergence of several factors: macroeconomic circumstances, technical advancements, and changing investor expectations. Due diligence, once a relatively standardized process, is now evolving to accommodate the shift. 

Key takeaways 

• Venture capital due diligence has evolved from gut-driven decision-making to a blend of structured and unstructured data analysis.
• VC due diligence is now more rigorous and data-driven in response to  macroeconomic pressures, rising LP expectations, and the proliferation of technology and AI tools.
• AI is transforming diligence by surfacing new signals, automating research, and enabling faster, more comprehensive assessments, especially with platforms like Affinity’s Deal Assist and Industry Insights.
• The result: fewer, but higher-quality deals, which strengthens the private capital ecosystem by increasing the likelihood of successful exits and future fund liquidity.

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Venture due diligence, before 

Historically, VC diligence was less structured and more reliant on personal networks, intuition, and a handful of standard checks. 

VCs often evaluated companies across all stages using similar criteria, relying heavily on founder reputation and warm introductions. The fate of a startup might be decided over the course of a long lunch, bypassing any deep data analysis. Investors prioritized speed over comprehensive intelligence in winning deals. After all, there simply wasn’t as much data to inform these decisions. 

But times have changed. 

“I’m not one to meet a company and give a term sheet within a week,” said Vanessa Larco, former Partner at NEA, in our recent webinar, Due diligence 2.0: Strategies for the AI era. 

“I like to spend a lot of time with founders, do a lot of references and back-channel references, and understand their growth and impact,” said Larco.

VCs today can make more informed, higher-conviction investments; so why wouldn’t they? 

How and why VC diligence is changing 

The VC landscape has shifted dramatically since the pre-pandemic era. There are several contributing factors at play. 

Macroeconomic forces

Post-COVID, higher interest rates and tighter capital markets mean that every dollar invested is under greater scrutiny. 

As Larco noted, “Each of the last few years has felt like it’s had its own headlining theme. First it was aggressive inflation, and then the rise of AI. Venture investing is becoming more specialized and sophisticated at every stage.”

This new reality is driving VCs to adopt stricter dealmaking criteria. Where once speed and gut instinct dominated, today’s investors are expected to demonstrate deeper diligence, not just to themselves but to increasingly demanding limited partners (LPs). LPs want to see robust data, clear signals of product-market fit, and evidence of founder growth potential before they commit capital.

In our recent private capital predictions report, we found that in today’s climate, 49% of investors use around four to six data sources to evaluate a single deal. 

Founder sophistication 

In tandem with curbing investor appetite for blind risk, founders are also growing more discerning. Today's entrepreneurs enter the fundraising process with greater knowledge, better networks, and higher expectations of their investors. This sophistication pushes VCs to refine their due diligence processes and demonstrate unique value beyond capital.

Larco told us, “Founders…are much more prepared for fundraising than I've seen when I first joined venture. They're going to look for the right partner for a specific stage, and the right partner for the next stage, and they're going to want to match the skill sets with what they need at that moment in time.”

On the flip side, founders and startups are held to higher standards. Early-stage diligence now emphasizes founder learning velocity and adaptability, not just resumes or references. Later-stage diligence will leverage richer datasets and assess risk in areas outside of simple revenue, like customer engagement and retention metrics.

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The role of AI 

Artificial intelligence has dramatically altered firms' ability to gather and process information. Our latest predictions report found that 64% of firms now use AI to accelerate company research, up from 55% the previous year. 

The capacity of AI to analyze vast and disparate datasets–from market trends and competitive intelligence to customer sentiment and regulatory filings–is transforming the speed and depth of due diligence. 

AI's influence also extends beyond mere data processing. It's becoming a tool for predictive analysis, enabling VCs to forecast future performance with greater accuracy and assess the long-term viability of a venture. With AI, VCs can identify patterns, anomalies, and potential risks that might be missed by human analysts. 

The modern, AI-enabled VC tech stack empowers investors to make decisions based on multiple layers of intelligence:

• Structured data: The analysis of traditional metrics—market size, product engagement, financials—for surfacing insights from vast data sets.
• Unstructured data: Qualitative sources—Reddit threads, social media, customer reviews—are mined at scale, providing a richer, real-time view of sentiment and product value.
• Signal discovery: AI helps investors codify and filter the “signals” that matter, enabling firms to focus on the right networks, founders, and markets.

Affinity's Deal Assist is one example of this evolution. It transforms deal notes, pitch decks, and diligence data into actionable insights while eliminating manual research time. Dealmakers can make faster, more confident investment decisions from the insights they unlock with AI. 

Centralization and collaboration 

One of the biggest challenges in modern diligence isn’t just gathering data, but organizing and sharing it across the firm. Affinity's Industry Insights helps address this by using AI to instantly generate competitive landscape analysis for target companies, providing firmographic and funding information.

As Larco put it, “Venture feedback loops are super long. It takes years to really develop the weights on which signals to look out for...The only way I’ve done it is by looking back at what has worked versus what hasn’t. If you can map that gut feeling you get from the founders with the more structured data that you actually have, I think that’s the next big unlock.”  

Today’s bottom line for venture due diligence 

All of these changes reflect a broader maturation of VC as a whole. The days of generalist investors moving freely between seed rounds and growth equity are giving way to more focused expertise. Investors now have stage-specific frameworks for evaluating companies. Blanket, one-size-fits-all due diligence doesn’t hold up. 

Will more thorough diligence result in fewer deals? Assuredly, yes. But these deals will be higher quality ones that are ultimately good for private capital. With every successful exit, more liquidity is pumped back into the ecosystem to be used in future funds. The end result is a healthy circulation of capital, innovation, and incentives in our sector. 

On the future of venture due diligence, Larco said, “The first principles still apply. We're still going to innovate, we're still going to have some of the brightest minds in software engineering launching new companies and taking that risk, and they're going to be looking for capital, they're going to look for early-stage investors.” Only now, the due diligence process will be more thorough, more specialized, and more data and AI-driven. 

As we see it, AI-powered diligence extends far beyond risk mitigation. It's the foundation for a more resilient, sustainable private capital ecosystem. There's tremendous value in gathering precise data, extracting meaningful signals, and bringing that intelligence together in one place. 

The Affinity CRM and its AI capabilities are purpose-built for exactly this challenge, transforming due diligence from a procedural checkbox into a genuine competitive advantage.

Elevating the venture due diligence process

Bring an exacting, intentional mindset to venture due diligence to reveal insights that others might miss. Here’s how to get started:

1. Codify your signals: Define what matters most — founder growth, product engagement, customer sentiment — and use AI to surface those signals from both structured and unstructured data.
2. Centralize knowledge: Use platforms that aggregate data, notes, and learnings, so your team’s collective intelligence compounds over time.
3. Balance speed and depth: AI can automate research and filtering, freeing up dealmakers to spend more time on high-value analysis and founder engagement.
4. Retrospect and refine: Regularly review past decisions and outcomes to calibrate your diligence process and signal weights. These feedback loops will pay dividends. 

To make sure you’ve covered all the bases, download Affinity’s complete VC due diligence checklist. 

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Venture capital due diligence FAQs

What are the stages of venture capital due diligence?

Venture capital due diligence typically unfolds across three critical stages:

1. Screening due diligence filters opportunities against the firm's investment thesis, eliminating poor fits before resources are committed—AI tools like Affinity's Industry Insights can dramatically accelerate this process by providing competitive landscape analysis.
2. Business due diligence examines market potential, product viability, business model strength, and team capabilities to evaluate growth potential and exit scenarios. 
3. Legal due diligence brings in legal counsel to verify company information, assess intellectual property, and identify potential risks before finalizing the investment decision. This step often requires 20+ hours per opportunity, but it’s important for confirming that firms will deploy capital with conviction, while protecting both the fund and its limited partners.

For a more comprehensive framework around the due diligence lifecycle, read our venture capital due diligence best practices guide. 

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How are traditional due diligence approaches changing?

Traditional diligence relied heavily on personal networks, references, and gut instinct. Today, it’s a blend of data-driven analysis (both quantitative and qualitative), AI-powered research, and ongoing process refinement.

What are some signs your diligence process needs to evolve?

• You’re relying on a single data source or anecdotal evidence.
• You’re missing out on high-potential deals due to slow or shallow research.
• Stakeholders are on different pages about the viability of an investment opportunity. 
• You’re unable to track or learn from past decisions and outcomes.
  

What are some signs that your venture due diligence process is going well?

• Documentation is collected and reviewed systematically, with few gaps or missing information.
• Your process gives an accurate picture of the startup’s health, including revenue growth, margins, burn rate, and cash flow.
• Your process identifies both current and potential risks (financial, operational, legal, regulatory, market) and assesses their impact and likelihood.
• The opportunities identified through due diligence align with the firm’s investment strategy, sector focus, and risk appetite.
• Information is communicated, shared, and stored in a central place where future stakeholders can access and learn from it.