Startups are increasingly using AI to handle legal and accounting tasks themselves, avoiding high professional fees. This signals a significant market need for tools that formalize and support this DIY approach, especially as startups scale and require more robust solutions for investors.

Instead of only investing in tech, Sequoia builds it. The firm employs as many developers as investors to create proprietary tools. This includes an AI system that summarizes business plans, analyzes team quality, and maps competitive dynamics, giving partners an immediate, data-rich overview of opportunities.

A new benchmark from the University of Oxford, VC-Bench, found that AI models like DeepSeek Chat can predict founder success (defined as a >$500M exit or raise) with 80% accuracy based on anonymized profiles. This starkly contrasts with the 23% accuracy of human VCs, questioning the notion that venture investing is an inimitable human art.

Resource-constrained startups are forgoing traditional hires like lawyers, instead using LLMs to analyze legal documents, identify unfavorable terms, and generate negotiation counter-arguments, saving significant legal fees in their first years.

Within the last year, legal AI tools have evolved from unimpressive novelties to systems capable of performing tasks like due diligence—worth hundreds of thousands of dollars—in minutes. This dramatic capability leap signals that the legal industry's business model faces imminent disruption as clients demand the efficiency gains.

Instead of paying lawyers $50,000 for deal diligence, Union Square Ventures' Fred Wilson used Google's free AI tool, NotebookLM. He uploaded past deal documents and the new startup's data room into separate "notebooks" and used AI to interrogate the differences, collapsing weeks of expensive work into a few hours.

Beyond automating data collection, investment firms can use AI to generate novel analytical frameworks. By asking AI to find new ways to plot and interpret data inputs, the team moves from rote data entry to higher-level analysis, using the technology as a creative and strategic partner.

AI tools can instantly parse, reformat, and summarize dense documents like congressional bills, which would otherwise require significant manual cleanup. This capability transforms workflows for analysts and researchers, reallocating time from tedious data preparation to high-value strategic analysis.

Venture capitalist Keith Rabois observes a new behavior: founders are using ChatGPT for initial legal research and then presenting those findings to challenge or verify the advice given by their expensive law firms, shifting the client-provider power dynamic.