TL;DR:
- Pitch decks flooding investors often miss the mark due to misalignment with investment criteria.
- Venture capitalists have specific investment theses encompassing factors like market size, founder profile, etc.
- Deckmatch, backed by €1 million funding, aims to streamline pitch evaluation using AI.
- Walid Mustapha, CTO, emphasizes AI’s role in categorically accepting or rejecting pitches based on theses.
- AI aims to add 60% to 70% value to an associate’s assessment, potentially becoming a virtual associate.
- Deckmatch converts unstructured data in pitch decks to structured filters aligned with VC criteria.
- Future plans include incorporating AI-informed market insights and data sources to enhance analysis.
- Léo Gasteen, CEO, envisions expanding the data flow to VC CRM systems with Deckmatch’s API-first design.
- The company’s closed beta test with 60 VCs validates its value proposition and guides further development.
- Funding injection will enhance AI capabilities, refine data analysis, and expand operations.
- Deckmatch envisions data-driven decision-making across various industries beyond VC.
- Shift toward data-driven processes could free up time for strategic endeavors and relationship-building.
Main AI News:
Navigating the intricate landscape of investment, one quickly realizes that a significant portion of the pitch decks flooding in is incongruous with the investor’s focus. Irrespective of their size, venture capitalists adhere to a defined investment thesis, encompassing factors like market dimensions, founder attributes, sectors, geographic scopes, ownership benchmarks, round magnitudes, and check sizes. This is the very essence of the VC realm. Should you direct a pre-seed stage gaming monetization presentation towards a growth-stage consumer tech fund, or funnel a growth-stage developer tool proposal to an early-stage hardware investor, you’re essentially squandering valuable time for all parties involved.
The primary defense against this deluge of decks often falls on the shoulders of associates within venture firms. According to Deckmatch, this layer of the process can now be delegated to an AI. Having secured a substantial €1 million ($1.1 million) funding round, the company is poised to transition its technology from the prototype lab to the expansive sphere of venture fund dealflows worldwide.
Walid Mustapha, CTO at Oslo and co-founder of Deckmatch, elucidates, “A significant portion of the value arises from categorical acceptance and rejection based on an investment thesis. This bedrock can be augmented by logical queries: How substantial is it? Does it intrigue you as a VC? Does it pioneer something distinctive in the current market milieu compared to the myriad of other proposals inundating you?” He continues, “Initially, we’re aiming to harness 60% to 70% of the value contributed by an associate. Eventually, our evolution could manifest as a bona fide associate role.”
The company’s initial phase revolves around transforming the unstructured data residing within a pitch deck into structured data, subsequently employed as a filter aligned with the VC’s criteria. The ambitions of Deckmatch extend beyond the information encapsulated within the pitch deck, envisaging an AI-guided estimation of market size and growth. Furthermore, the company endeavors to integrate other data sources, thereby enriching the investment analysis.
Léo Gasteen, CEO at Deckmatch, sheds light on their approach: “If the pitch deck serves as one piece of the mosaic, what other pieces can we acquire? This prompts the question – what insights can be gleaned from the vast expanse of the web? What narrative can we weave?” Gasteen adds, “Subsequently, our focus pivots towards streamlining the data flow to its intended destination: the VC’s CRM system. DeckMatch is inherently designed as an API-first solution.”
The company has already undergone a closed beta test, collaborating with approximately 60 VCs to substantiate its value proposition. Their incoming funding injection will be allocated towards advancing their AI and machine learning capabilities, refining the algorithms underpinning data analysis, enhancing their technological infrastructure, and expanding their operational footprint.
While Deckmatch currently targets VC firms and their pitch decks, their ambitions extend beyond these boundaries. Their vision encompasses broader sectors such as recruitment and procurement. As Léo Gasteen envisions, “We foresee a future in which decision-making processes across diverse industries, including venture capital, adopt a data-driven approach. This would liberate time for strategic, imaginative, and human-centered pursuits, such as decision-making and relationship cultivation.” He concludes, “The evolution within the VC domain, transitioning from pen and paper to Word and Excel, represents perhaps the most monumental transformation the industry has encountered. The intriguing paradox is that VCs, although catalysts of change, sometimes resist it. We express our gratitude to our early investors, as their support will empower us to refine, enhance, and expand our product while bolstering our team.”
Conclusion:
Deckmatch’s AI-driven approach addresses the misalignment between pitch decks and investor criteria. Their technology, capable of mimicking associate evaluations, holds the potential to reshape investment evaluation processes. The expansion into diverse industries indicates a broader trend towards data-centric decision-making, redefining the role of venture capitalists in the evolving business landscape.
