Maywood Automates Deal Execution So Junior Bankers Can Stop Building Decks at 2 AM

The Macro: Investment Banking Runs on Manual Labor and Sleep Deprivation

Investment banking is one of the last professional services industries that runs on pure manual effort. Junior bankers spend 80 to 100 hours per week building PowerPoint presentations, populating financial models, compiling data rooms, and responding to due diligence questions. A single M&A deal might require hundreds of slides, dozens of financial schedules, and thousands of pages of diligence documents.

The tools have barely changed in decades. PowerPoint. Excel. Word. Email. The most technologically advanced thing in most banking workflows is a proprietary template library that ensures the firm’s logo is in the right corner.

This matters because the output is not creative work. Most of what junior bankers produce is formulaic. A Confidential Information Memorandum follows a standard structure. A pitch deck for a sell-side mandate uses the same frameworks every time. Financial models follow predictable patterns based on the industry and transaction type. The work is time-consuming because of volume and formatting requirements, not because it requires novel thinking.

AI should excel at exactly this kind of structured, template-driven document generation. But investment banks are notoriously conservative about adopting new technology, especially for client-facing deliverables where errors are career-ending.

Maywood, backed by Y Combinator, is building the AI platform that investment banks will actually trust for deal execution.

The Micro: Blackstone, MIT, and BCG Alumni Building for Banks

Drake Goodman (CEO) worked at Blackstone in private equity and graduated from the Huntsman Program at Wharton. Kent Goodman studied at MIT and worked at BCG on automation. Esteban Vizcaino (CTO) has AI and ML research experience from Balyasny hedge fund. The team understands both the banking workflow and the technology needed to automate it.

The platform generates finished, on-brand deliverables: CIMs, pitch decks, teasers, memos, and financial models. The emphasis on “finished” and “on-brand” is important. Investment banks will not use a tool that produces drafts requiring significant manual cleanup. The output needs to look like it was produced by an experienced analyst who knows the firm’s formatting standards.

The editability and auditability features address a critical banking requirement. Bankers need to modify generated content and track what was changed. A black-box tool that produces un-editable output is a non-starter in banking.

SOC 2 Type II, GDPR, and CCPA compliance (with ISO 27001 and ISO 42001 in process) address the security concerns that are the primary blocker for technology adoption in banking. Deal information is among the most sensitive data in finance, and banks will not send it to a platform that does not meet rigorous security standards.

Customer testimonials claim Maywood “doubled team capacity” and put firms on pace to “double deal count next year.” If accurate, this represents the kind of productivity improvement that justifies premium pricing.

Competitors include Artic (AI for banking presentations), various AI writing assistants adapted for finance, and internal tools built by larger banks. Maywood’s advantage is the purpose-built platform that handles the full deal workflow rather than individual document types.

The Verdict

Maywood is targeting the right market with the right team credentials. Investment banking deal execution is ripe for AI automation, and the team’s banking experience creates credibility with buyers.

At 30 days: how many deals are being executed with Maywood-generated deliverables at client-facing quality?

At 60 days: what is the typical time savings per deal, and does it free up capacity for more deal flow?

At 90 days: are mid-market banks adopting Maywood as a competitive advantage against larger firms?

I think Maywood has strong product-market fit. The investment banking workflow is structured enough for AI to automate effectively, and the labor cost savings are enormous. If the output quality meets banking standards, Maywood transforms how deals get done. The Blackstone pedigree on the founding team opens doors that other AI startups cannot.