SaaStr.ai Launches VC Research & Matching: Here’s How It Works

We just shipped a new AI-powered feature on SaaStr.ai that matches founders with VCs based on their actual investment criteria.

What It Does

You input your startup metrics—ARR, growth rate, stage. The system analyzes your profile against 361+ top B2B + AI VCs firms in the SaaStr ecosyem, then shows you which ones actually invest in companies like yours.

The matching considers:

• Check size – If you’re raising $5M, you won’t see firms that only write $25M+ checks
• Stage focus – Series A companies get matched with early-stage investors, not growth equity firms
• Geography – US-only funds don’t show up for European companies unless they invest globally
• Sector – The system shows each VC’s actual portfolio so you can see if they back companies in your space
• Growth profile – High-growth companies get matched with different investors than steady-growth businesses

The Fundability Score

Before you see your matches, you get a Fundability Score based on your metrics.

The system benchmarks your growth rate against other companies at your ARR. In the screenshot above, a company doing $50M ARR with 150% growth gets 100% because that growth “significantly exceeds the 90% top quartile benchmark for $50.0M ARR companies.”

If you’re growing 40% at $50M ARR, you’ll see you’re below the benchmark. Not unfundable, but you need to know that going in.

This tells you whether your metrics are competitive before you start pitching.

The Match Results

For each VC, you see:

Basic criteria:

• Check size range ($50M-$200M for Iconiq, $10M-$300M for TCV)
• Stage focus (Series C+, Series B-D, etc.)
• Geographic focus (North America, Europe, Global, US)

Portfolio examples:

• Iconiq: Snowflake, Uber
• TCV: Airbnb, Netflix
• Hg Capital: Visma, IFS Software Group

Fit percentage:

• 100% Fit means you match their stated investment criteria across all dimensions
• Lower percentages show partial fit (right stage but wrong geo, right sector but wrong check size, etc.)

How to Use It

• Step 1: Go to the Research AI+B2B VCs page and input more about your startup.  Your metrics and what you di.
• Step 2: Review your Fundability Score. If you’re below benchmark, you may want to wait another quarter or two before raising. If you’re at or above benchmark, you’re competitive.
• Step 3: Look at your Top 25 matches. Click through to see each firm’s portfolio and investment criteria.
• Step 4: Prioritize VCs where your metrics align and they’ve backed similar companies. Those are your highest-probability targets.
• Step 5: Upload your pitch deck when you are ready.  We’ll grade it, give you feedback, and if you’re ready — connect you directly with the VCs!

The Data Behind It

We’ve processed 2,200+ pitch decks per month through SaaStr.ai VC in less than 60 days! The benchmarking data comes from analyzing thousands of funded companies to understand what growth rates and metrics are actually competitive at each ARR band.

The VC criteria comes from public portfolio data, stated investment focus, and actual check sizes written — and our data on 5,000+ closed rounds. When a firm says “Series B-D” but their last 10 investments were all Series C, the data reflects what they actually do, not just what they say.

What This Solves

The traditional fundraising approach: Research 60+ VCs individually, customize outreach for each, send emails, maybe 20 respond, take 10 meetings, 2 invest.

Timeline: 8-12 weeks. Conversion rate: 3-4%.

With VC matching: Get 25 high-fit VCs instantly, focus on the 15 that match best, 10+ respond, take 8 meetings, 3 invest.

Timeline: 4-6 weeks. Conversion rate: 12-15%.

You spend less time researching, less time on low-probability pitches, and more time with VCs who actually write checks for companies at your stage and scale.

Pricing

Free to use. Input your metrics, get your score and matches. No credit card required.

If you upload your deck for deeper analysis through our pitch deck analyzer (which we’ve processed 1,200+ times), that’s part of our broader SaaStr.ai toolset.

Why We Built This

As a VC, I take ~400 pitches per year. Maybe 30 are actually in my investment focus (Series A/B B2B SaaS). The other 370 are wasting both our time—too early, too late, wrong sector, wrong geography.

From the founder side, I’ve watched companies with great metrics struggle to raise because they were pitching the wrong investors. Not because the business wasn’t fundable. Because they were talking to VCs who don’t invest in their stage or space.

The matching engine solves both problems. Founders focus on high-probability targets. VCs get fewer irrelevant pitches.

The result: Faster fundraising, higher close rates, less wasted time on both sides.

The Bottom Line

Fundraising is a numbers game. But playing it intelligently—25 right-fit VCs instead of 60 random ones—changes the entire equation.

You can’t control whether a VC says yes. But you can control whether you’re pitching VCs who actually invest in companies like yours.

That’s what this does.

Try it: Go to SaaStr.ai, input your metrics, see your matches. Takes 60 seconds.