Maywood

Core Problem

Dealmaking in investment banking, private equity, and corporate development is characterized by highly manual, document-intensive, and repetitive tasks. Professionals spend a disproportionate amount of time drafting Confidential Information Memorandums (CIMs), pitch decks, and financial models, as well as managing diligence responses. This reliance on manual labor creates significant capacity constraints, where skilled teams are bogged down by administrative drafting rather than focusing on high-level strategy and client relationships. Furthermore, the process of synthesizing data from disparate sources—such as emails, filings, and internal databases—is prone to human error and limits the overall deal throughput of a firm.

Maywood’s Solution

Maywood provides a purpose-built AI platform designed to automate the entire deal execution lifecycle. Unlike generic AI tools, Maywood is specifically engineered for the M&A environment, connecting directly to a firm’s "digital universe," including files, folders, emails, meetings, and external data vendors. The platform uses this integrated data to instantly generate and iterate on critical deal materials like CIMs, teasers, and diligence responses. A key differentiator of the solution is its focus on editability and auditability, ensuring that the AI-generated outputs can be refined by professionals and traced back to source data for compliance and accuracy.

Value Proposition

• Increased Capacity: Maywood claims to help teams double their deal capacity without increasing headcount, effectively turning time-consuming drafting into a streamlined automated process.
• Quality and Speed: The platform generates on-brand, high-quality presentations and models much faster than manual methods, allowing firms to move from origination to close with greater velocity.
• Security and Integration: By integrating with existing enterprise tools and maintaining high security standards (SOC2/GDPR), Maywood reduces the friction of data silos while ensuring that sensitive financial information remains protected. This combination of efficiency and enterprise-grade reliability makes it a compelling solution for regulated financial environments.

Market Landscape and Trends

The market for M&A technology is undergoing a significant shift from passive storage solutions to active, AI-driven workspaces. Traditionally dominated by Virtual Data Rooms (VDRs) used for secure document storage, the industry is now demanding end-to-end platforms that can synthesize data and automate the creation of deal materials. Key trends include the rapid adoption of generative AI for drafting, a heightened focus on enterprise-grade security (SOC2/GDPR), and the integration of fragmented data sources into a single 'source of truth' for deal teams.

Key Competitors and Adjacent Vendors

Maywood competes with both established incumbents and emerging AI-specialized startups:

• Established VDR Giants: Companies like Datasite and SS&C Intralinks are the market leaders in secure document management. While they are adding AI features, their primary value remains in the VDR infrastructure.
• Deal Management Platforms: DealRoom, Midaxo, and DealCloud focus on project management and CRM for M&A, helping teams track the progress of transactions.
• Specialized VDR/Diligence Providers: Vendors such as Ansarada, iDeals, and Firmex provide targeted solutions for specific transaction types or mid-market deals.
• AI-First Competitors: Newer entrants like Blueflame AI and Grata focus on AI-driven research and automation, directly challenging Maywood in the space of intelligent deal sourcing and drafting.

Competitive Advantages and Risks

Advantages: Maywood’s primary advantage is its deep integration with a firm’s internal digital ecosystem (emails, meetings, files), allowing it to generate more context-aware and accurate drafts than generic tools. Its founding team’s mix of Blackstone-level finance experience and MIT engineering talent provides a unique blend of domain expertise and technical capability. Furthermore, its focus on 'editability and auditability' addresses a critical pain point for financial professionals who need to trust and verify AI-generated content.

Risks: The main challenge for Maywood is incumbent entrenchment. Large banks and PE firms often have long-term, enterprise-wide contracts with established players like Datasite or Intralinks. Overcoming the 'switching cost' and proving that a startup can meet the rigorous security and compliance standards of global financial institutions will be critical for long-term success.

Founders and Background

Drake Goodman — Co-founder & CEO Drake Goodman serves as the co-founder and CEO of Maywood. His professional background includes a tenure at Blackstone, providing him with direct experience in the private markets and investment banking sectors the company targets. He holds strong academic credentials from the University of Pennsylvania and the Wharton School, where he participated in the prestigious Huntsman Program. His academic record is distinguished by honors such as summa cum laude and membership in Beta Gamma Sigma, alongside leadership recognition during his student career. Drake’s expertise focuses on dealmaking and product/market strategy for M&A workflows.

Kent Goodman — Co-founder Kent Goodman is a co-founder of Maywood with a background in management consulting, having previously worked at Boston Consulting Group (BCG). He possesses a technical and business-oriented academic foundation from the Massachusetts Institute of Technology (MIT), where he studied Electrical Engineering and Computer Science (EECS) and attended the Sloan School of Management. His professional activity indicates a focus on technical and product leadership, bridging the gap between complex engineering and business strategy.

Esteban Vizcaíno — Co-founder & CTO Esteban Vizcaíno is the co-founder and CTO of Maywood, leading the company's engineering and AI development. He earned a degree in EECS from MIT, a credential that supports his role in building a sophisticated AI-driven platform. His background is marked by significant early recognition, including being named a Dominion Energy Equity Scholar and a National Hispanic Scholar. His experience includes research roles and engineering leadership, which are critical for developing the automated deal execution tools that define Maywood’s product offering.

Summary The founding team effectively combines domain expertise in investment banking and private markets (Drake), strategic consulting and product management (Kent), and deep technical expertise in AI and computer science (Esteban). As an active Y Combinator Winter 2026 company based in New York, Maywood is positioned to leverage this multidisciplinary leadership to disrupt traditional M&A workflows through purpose-built software automation.