From Data To Capital: Orbita.vc Founder Daniil Kirikov Explores How VCs Can Harness AI

Algorithms can streamline VC responsibilities, making them less time-consuming, and lead to cost savings while mitigating investment risks and reducing due diligence time by up to 50%. With its robust data analytics and predictive capabilities, Artificial Intelligence promises to redefine how VCs operate. Daniil Kirikov, the founder of Orbita.vc, talks about how AI can reshape the operations of venture capitalists and suggests sample prompts that they can employ to enhance their efficiency.

Growing at a 36.2% CAGR, the AI market is projected to hit the $407B mark by 2027. Daniil Kirikov emphasizes: “If you've spent enough time online, you're familiar with the most popular use cases. Generative text-to-image and text-to-text. Months ago, after the publication of the research paper GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models, we all figured out that 80% of jobs could change. Forever. And VCs are no exception”.

According to Orbita.vc, AI does help the VC ecosystem, though. From market analysis, brainstorming, and scoring all the way down to decision augmentation, accelerated due diligence, and report summarization.

Thanks to AI's vast datasets, you can turn VC responsibilities into less time-consuming to-dos. Depending on the firm size, the goal is to either save operational costs or time on paperwork while thinking about investment risk. You're in the business of creating scalable businesses. So having these aspects sorted lets you reallocate efforts to make your portfolio shine.

Venture Capital—Artificial Intelligence Intersection

Here's the problem VCs often face: lack of real-time project control on what's going on. Since you don't have tasks or an operating base, there's no vision on the company's activity.

What if, instead of staying blindly unaware until the next stakeholder meeting, you use AI?

Based on the project management system your startup has in place, set up ongoing report notifications. Then make AI summarize the information with full-scale stats on what's happening right now – the good, the bad, and the ugly – and how to solve it.

“In the startup funding equation, the two time-consuming parts are validation and due diligence. Validation because it's reviewing the never-ending incoming pitches along with expert evaluation. And due diligence, where once venture capitalists show interest in a project, negotiation, and terms begin to close the deal. As soon as possible,” says Daniil Kirikov. 

For investment funds with at least 20+ projects, AI can reduce due diligence time up to 50%.

So the AI-VC intersection ends up…

• • Cutting operational costs. AI's ability to process data reduces the workload of human analysts. Faster reporting streamlines decision-making, enhances the quality of routine tasks, and frees up talent for new assignments. Every dollar counts.
  • Saving funding process time. Imagine a super assistant that cross-checks data making sure ventures align with expectations. It speeds up the pitch-to-partnership process. In both phases respectively, validation and due diligence.
  • Reducing investment risk. To err is human. Even the best of us can miss patterns. But when it comes to startup investing—the better the intel, the safer the bet. With AI data analysis, spotting overlooked pitfalls early on is a true game changer.

Potential AI Use Cases for VCs

According to Orbita.vc, the Venture Capital landscape, traditionally driven by human intuition and experience, is undergoing a transformation. Artificial Intelligence, with its robust data analytics and predictive capabilities, can redefine how VCs operate. Whether it's spotting market trends, evaluating startup potential, or streamlining due diligence, AI can show up use cases that can substantially augment the decision-making of investors.

1. Market analysis

One of the options for how VCs can use AI is market analysis, which can comb through vast amounts of data to identify dominant patterns, emerging industries, and evolving consumer needs. This can help to adapt investment decisions based on market traction and sectoral growth analysis.

Prompt example: "Using data from the past 2020-2023, analyze global tech market trends, especially focusing on health tech, ed-tech, and greentech sectors. Break down the market share, growth rates, emerging players, and potential disruptors."

2. Idea brainstorming

As Orbita.vc states, artificial intelligence can help VCs recognize unmet needs in the market. By training AI models on current problems and market gaps, they can generate potential solutions that cater to these challenges, aiding in idea generation for new startups or pivots for existing ones.

Prompt example: "Considering the major challenges faced by remote workers such as network instability, collaboration difficulties, and time-zone differences, propose innovative tech solutions or platforms that startups can develop."

3. Startup scoring

By setting parameters, AI can streamline the assessment of startups, making the process more consistent and data-driven. It can also pull data from multiple sources, ensuring a holistic review of each startup's potential.

Prompt example: "Evaluate each startup based on 3 primary factors: market potential (analyze target market size and growth), team expertise (check the background and past ventures), and innovation (assess product's uniqueness and potential to disrupt). Provide a score out of 100."

4. Profit forecasting

Predictive analytics and machine learning models can be used to make more accurate profit forecasts. By analyzing historical data and market trends, AI can provide nuanced insights into potential forecasting, and Orbita.vc’s founder Daniil Kirikov proves it’s not just accurate, but helps to speed up this part of the analysis. 

Prompt example: "Examine [company]'s operational performance over the last three years, factoring in revenue growth, spending trends, market expansion, and industry shifts. Predict the potential operational performance for [year]."

5. Decision augmentation

AI can enhance decision-making by providing objective insights based on vast datasets. It can augment the intuition and experience of VCs with hard data, ensuring a comprehensive assessment of potential investments.

Prompt example: "Examine available data on the growth trajectory and user reception of [AI-based mental health apps]. Considering their effectiveness, market size, and competition, provide a detailed recommendation on investment viability."

6. Accelerated due diligence

With automated tools that can swiftly analyze vast amounts of data, Orbita.vc states, VCs can expedite their due diligence process. Such systems can instantly highlight discrepancies, potential risks, and growth opportunities, making the investment process more efficient.

Prompt example: "Review [company]'s available financial statements, founder and team credentials, intellectual property, and any legal issues. Provide a comprehensive due diligence report, highlighting any potential red flags."

7. Report summarization

AI-driven summarization tools can condense reports into actionable insights, allowing VCs to grasp the essentials of a company's performance and plans, saving them precious time.

Prompt example: "From [company]'s [year] annual report, extract key achievements, financial milestones, challenges faced, and strategic initiatives for the next year. Write a concise summary without missing critical information."

Investing in startups is as much an art as it is a science. While the future remains unpredictable, AI can help illuminate paths not previously considered. In the rapidly evolving world of investments, staying ahead means integrating advanced technologies into the investment process. And for VCs working with returns and risks, AI might be the partner they've been waiting for, as demonstrated by Daniil Kirikov and Orbita.vc.

This post was authored by an external contributor and does not represent Benzinga's opinions and has not been edited for content. The information contained above is provided for informational and educational purposes only, and nothing contained herein should be construed as investment advice. Benzinga does not make any recommendation to buy or sell any security or any representation about the financial condition of any company.