V7 Team
Years ago, V7's CEO Alberto Rizzoli was an intern at a bank. Incidentally, his experience there would become part of the blueprint for the AI company he later built.
"I was disenchanted by the amount of manual work that has to happen. Going through tons and tons of documents, looking through numbers in a tedious and somewhat repetitive way," Rizzoli recalled.
That experience isn't unique. It highlights a fundamental inefficiency in private equity: skilled professionals spend their days buried in tedious, repetitive tasks. It's a huge drag on operations, and it's precisely the problem generative AI tools can now solve.
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From a Full Day's Work to an Hour's Task
The most immediate win for AI in the investment lifecycle is in automated due diligence. Damien Fietta from Eurazeo gave a powerful example of what this means for his firm.
"AI tools are now helping us to generate documents," he explained. "When we have access to a VDR, AI can generate the first draft of our memo. It's been incredibly helpful."
Compressing a full day of an analyst's work into a task that takes less than an hour is the kind of high-impact automation platforms like V7 Go are designed for. This lets the human team focus on what they do best: verification, strategic thinking, and asking tough questions.
Alberto explained how this same approach applies across the entire deal lifecycle:
Proactive Deal Sourcing: AI Agents can be deployed to scan the market for you. "Every week or every day, they can look at companies' LinkedIn profiles to see if the employee count has changed," Alberto suggested. "They could go to the Twitter profiles of the founders and so on. All of these signals are out there on the internet, and AI will help us unlock them."
Due Diligence: Once a target is identified, analysts face a mountain of documents in the virtual data room. AI tools for M&A due diligence can ingest this entire repository, reading every contract and financial statement to extract key metrics and flag potential risks. With AI handling the manual work, the analyst's role shifts from data miner to strategic reviewer.
Intelligent Portfolio Monitoring: Managing existing investments often means fighting with siloed information and manual CRM updates. This is where V7 Go's Knowledge Hubs feature comes in. "You want to aggregate portfolio company data in a place that isn't just a CRM where you have to manually do data entry," Alberto noted. The technology automatically indexes key metrics, making portfolio information instantly searchable and cutting out the administrative headache.
Black Boxes and Trusting the Machine
No one in finance is going to blindly trust a "black box." For AI to be useful in high-stakes decisions, you have to see how it reached its conclusions. Alberto was blunt about this.
"If it's too much of a black box, the first time you see an answer that is incorrect or dubious without the ability to trace back how it got there, that's when you stop trusting AI," he stated. "And that's usually what kills the adoption process."
He explained that this principle is built directly into V7 Go through features like AI Citations, which visually link every extracted data point back to its source. This creates a human-AI partnership where professionals can quickly verify the machine's work.
Michael O’Sullivan from Moonfare, a veteran of the markets, emphasized this point. He stressed that technology complements, but never replaces, the human element of investing. "The speed at which I can understand the company and its success has never been faster," he said.
Get Started by Experimenting
Looking ahead, Alberto sees a future where interacting with financial data is completely seamless—a vision he's building with AI Agents powered by V7 Go. "My dream is that when we go for our next round of fundraising, it's all going to be done through V7 Go," he shared. "Our data room will be easily navigable... you can ask any questions and get any statistics that you need in graph form."
For firms that haven't started their AI journey, his advice was simple: don't wait for the perfect plan. Start experimenting.
"It's somewhat counterintuitive, but you learn a lot more by building something first. That process unlocks the actual use cases that you want to solve one or two projects down the road," he explained. "I would encourage people to jump into proof of concepts before you feel like you're ready or you've identified the perfect use case. It's better to learn through hands-on experience than to start from scratch."
To learn more about how specialized AI agents can accelerate your firm's operations and handle complex document workflows, book a demo of V7 Go today.
