Can AI Democratize Venture Fundraising?

Since the explosive debut of the modern AI era, experts have marvelled at its potential to redefine the entrepreneurial experience, streamlining everything from hiring to administration to marketing.

Jennifer Ai is working to add another capability to the list: demystifying and democratizing the often opaque — and usually inefficient — process of startup fundraising.

Ai (yes, that is her real surname) is currently leading Leopard AI, a Toronto-headquartered upstart — her third in the AI space — that she started in 2024. The company is building a proprietary AI and machine learning platform that allows all players in the startup ecosystem — early-stage founders, venture capital professionals and government and institutional partners — to quickly access credible and verifiable information about one another. It’s meant to serve as “trust infrastructure” that accelerates a process that typically takes far more time and energy than the parties involved would like. 

Ai cut her teeth in institutional finance after graduating from the Smith Master of Management Analytics program. During her time working at some of Canada’s biggest banks she was able to see firsthand how AI and data were transforming finance: on trading floors, in lending portfolios, in market science, and in global risk management. “I kept thinking: ‘If we can use this technology for the big banks, why can’t we do it for every business, and everyone?’” 

This led to her starting her first AI technology business. From there she had a front-row seat to the brokenness of early-stage capital markets. She saw systemic failure and a unique chance to solve it. Ai spoke with Smith Business Insight contributor Deborah Aarts about why it’s still so hard for founders and funders to align today, and how AI can help make the process better for all.

What’s so broken about the venture fundraising process?

Fundraising can be a make-or-break moment for ventures, and there’s so little known about who to talk to, and in which sequence, and in what context. No one talks about it and the stakes are very high if you do it wrong.

Once I found myself in the black box, I saw so many barriers. I discovered that founders had no transparency into what investors were actually looking for: They were left to craft pitch decks in a vacuum, guess at what metrics mattered and hope someone would bite. They had no visibility. Even if they were building a great company, they couldn’t easily prove it and had to reset every time they walked into a new investor meeting. There was a massive network barrier. Venture capital is still a relationship-driven business and if you don’t know the right people, you’re invisible, even with a great idea. This disproportionately disadvantages founders from underrepresented groups, rural communities and emerging markets.

I saw the inefficiency of a process that was manual, slow and expensive, with founders spending more than 1,000 hours raising a single round, investors spending months on due diligence. I saw a trust barrier, where when investors can’t verify information, they say ‘no’ more than ‘yes,’ which is what leads to a situation where investors sit on a lot of dry powder — as in, hundreds of billions of dollars. Essentially, I saw an ecosystem lacking the fundamental infrastructure to fund or trust new businesses.

How do you think it got to this point?  

From my perspective, the root cause of the problem is information asymmetry, combined with a trust deficit. The lack of standardized, credible data on founder integrity, execution capability and project viability makes investors default to risk aversion. And the lack of transparency about capital availability and investor criteria makes founders waste months chasing the wrong doors. It also leads to investors and founders complaining about one another, in what can be a very toxic environment, just because they don’t have a mechanism to get to know each other.

How did you decide to get involved in improving the situation?

The more I learned about the problem, the more I started to think I might be able to solve it, given my technical background and my experiences in finance, in entrepreneurship and, of course, in trying to fundraise. Moreover, it was a problem I could wake up excited to solve every day. I think founders and innovators are the hope of our society — I could talk to them 24/7 — and the idea of making their lives easier really excited me.

I realized that the problems involved in fundraising were ones that consumer finance had solved 50 years ago, with the creation of credit bureaus. Venture capital never had anything like that. I wondered if AI could make it possible. 

Fast-forward to now: How does the solution you’ve built with Leopard AI work? 

Practically, founders can engage with our platform from the moment they start building, providing information about the company, team, technology, financials and more. This creates an ongoing context layer, a sort of living profile of the company that updates in real time. Our agentic AI systems track, verify and enhance information about the company from verifiable sources, based not only on self-reported data, but also on founder activity, technology developments and operating milestones. Our algorithms evaluate and summarize what we call ‘trust track records’ in real time, providing forward-looking assessments that measure things like execution velocity, project integrity and technology safety. 

On the investor side, investors can access always-on, transparent, explainable credibility profiles with verifiable sources and traceable evidence. This intelligence reduces the time and cost of due diligence before they even meet the founder.

We are not a matching tool. There are plenty of platforms that connect founders and investors. We are infrastructure, the governance layer that makes those connections trustable, efficient and fair. Everyone in the ecosystem benefits.

Beyond the benefits to founders and investors, are there other reasons to democratize intelligence about venture fundraising?

Just within Canada, the cost of the current system to our economy is brutal. Early-stage startups die at make-or-break moments, not because their ideas lack merit, but because they can’t secure capital. Talented entrepreneurs who could build transformative companies instead leave Canada or abandon their ventures. A generation of innovators watches opportunity evaporate and chooses safer paths. This represents a massive opportunity cost. Canada loses not just companies, but intellectual property, jobs and the compounding returns that early bets on innovation can create.

We’ve also created an unequal playing field where founders with networks access capital, while others are invisible, regardless of merit.

These problems have been decades in the making, but they’ve become urgent now. 

We’re entering the autonomous AI era, where AI agents act independently — making decisions, executing tasks, interacting with systems. This creates enormous opportunities but also enormous risks, especially when it comes to investment decisions. We see ourselves as building safety guardrails for the autonomous economy. 

What excites you most about how AI is changing fundraising?

We’re in the middle of a global entrepreneurial boom. More than 10 million new businesses launch each year, and that number is accelerating. The next generation is full of agency, autonomy and creativity. They’re going to build world-changing companies. We are building the infrastructure to fund them efficiently, fairly and safely. We’re working to fix this problem, once and for all, so that all the next generations of founders don’t need to go through what I’ve been through in the dark.

Every founder deserves a fair shot, regardless of their network, geography or background.