Video Library

PitchBook AI turns private-market research into a finished work product — defined the way you want it.

Watch how it generates shareable, customizable artifacts directly from PitchBook Skills, refines content conversationally, and saves your preferred output as a repeatable Skill you can reuse and automate with Agents.

Grounded in PitchBook’s trusted private-market intelligence, with reasoning and sources shown transparently, it lets you define what good looks like once and make it repeatable.

PitchBook gives allocators and institutional investors the tools to benchmark fund performance against relevant peer groups, assess manager track records across strategy, vintage, and geography with Manager Scoring, and analyze commitment activity by LP type, location, AUM, and strategy.

Whether you’re evaluating a first-time fund or reassessing an existing relationship, PitchBook puts the market’s most trusted private capital data at your fingertips.

See for yourself: https://pitchbook.com/tour/allocation

PitchBooks VC Exit Predictor makes it easy to synthesize our best-in-class venture market data, providing exit trajectories and investment comparisons for VC-backed companies.

We treat our customers like royalty at PitchBook, and we believe our communities deserve the same.

Though the tech industry is on track to spend nearly $600 billion on AI infrastructure in 2026, M&A is hardly part of that equation. The Big Five of Google, Meta, Microsoft, Amazon, and Apple, dropped from thirty-three acquisitions in 2017 to only twelve in 2026 YTD, showing a growing preference for back and build strategies.

Why are the industry’s most influential, cash-rich companies not buying startups and what does it mean for AI M&A? Find out with insights from PitchBook’s Senior VC Analyst Kaidi Gao who looks at key players in this trend and their motives.

The PitchBook VC Exit Predictor gives you insight into whether, and now when, a portfolio company may exit. This video outlines the full VC Exit Predictor workflow and demonstrates how to build a systematic view of where liquidity is most likely to materialize. Get ahead of LP conversations and sharpen reserve decisions, across a single company or your entire portfolio. Explore the VC Exit Predictor on any VC-backed company profile.

Every GP is being pitched on AI, but most tools pull from incomplete data. In private markets, an incomplete picture is a real liability. In this video, Kyle Stanford, CAIA, Director of US Venture Capital Research at PitchBook, shows how PitchBook’s LLM partnerships connect our dataset to the AI platforms GPs already work in, including Claude, ChatGPT, Microsoft 365 Copilot, and Perplexity. Whether you’re sourcing new targets, running diligence, or tracking a portfolio company toward exit, ask a question in plain English and get an answer grounded in PitchBook’s data, right inside your existing workflow.

The exit environment has been under pressure for years: IPO windows are narrow and M&A timelines stretch. For a GP, the question isn’t just which companies will exit, but which are ready and when. In this video, Kyle Stanford, CAIA, Director of US Venture Capital Research at PitchBook, shows how the VC Exit Predictor gives each company a probability estimate of exit within a given time horizon, built through machine learning on PitchBook’s data. See how GPs compare companies across a portfolio, track how scores move over time, and get ahead of which companies need attention before the exit window opens.

Valuation is one of the hardest calls in venture — no public price, incomplete comps, and a market that moves before a deal even closes. In this video, Kyle Stanford, CAIA, Director of US Venture Capital Research at PitchBook, shows how GPs use Valuation Estimates to price investments with model-backed ranges built on PitchBook’s proprietary data and analyst IP. See how GPs apply that range beyond a single deal: pricing new investments with more confidence, monitoring valuation risk across a portfolio, and modeling fund-level performance without waiting on stale comps.