PitchLens

What Menlo Ventures looks for in a pitch deck

Menlo Ventures is a 50-year-old early-stage firm that has gone 'ALL IN on AI,' investing across the full stack from infrastructure and frontier models to AI-native applications in enterprise, healthcare, and consumer. Their conviction signature is backing founders 'before the opportunity is obvious'—they invested in Anthropic in 2023 when it was pre-product and pre-revenue, then led its Series D. They pair deep technical and operational expertise with hands-on company-building, and ground their theses in their own annual State of Generative AI in the Enterprise research.

Stage focus: pre-seed, seed, Series A · Sectors: artificial intelligence, ai infrastructure, foundation models, ai native applications, enterprise software, developer tools, cybersecurity, healthcare

What Menlo Ventures wants on each slide

Problem

A clearly defined problem paired with a unique insight into why it matters—not merely that the problem exists. Quantify the spend or pain it represents.

“At the core of any successful business is a problem that needs to be solved. Your pitch should clearly define the problem and provide unique insights into why it matters.” — Refine Your Business Idea: Our Elevator Pitch for Future Founders
“Enterprises spend over $150 billion annually on customer success and support, yet only 5% (~$10B) goes to software.” — Tim Tully

Solution

A high-level, clearly differentiated solution; at the earliest stage keep it high-level because it will evolve. The best products find value beyond their intended use case.

“Finally, you need to have a vision for your high-level solution and how it's differentiated from existing solutions. The key for very early business concepts is to keep it high-level; at this stage the idea is bound to evolve.” — Refine Your Business Idea: Our Elevator Pitch for Future Founders
“This is the mark of truly transformative software: when it finds use cases beyond its intended audience, creating value in unexpected places.” — Tim Tully
“AI inference can become dramatically more efficient by decoupling AI workloads from specific hardware, decomposing them into constituent stages, and routing each to optimal compute.” — Tim Tully

Market size

A specific, well-defined target market and an enormous or fast-growing opportunity—ideally one they can size with their own enterprise-AI data showing it growing faster than any software category in history.

“Your target market is the specific group of people or businesses that your product or service serves. It's important to define the buyer or user.” — Refine Your Business Idea: Our Elevator Pitch for Future Founders
“Enterprise AI is the fastest-scaling software category in history” — 2025: The State of Generative AI in the Enterprise
“We want to help create products and services that improve peoples' lives and disrupt or create enormous markets and result in iconic, world-changing companies.” — Mark Siegel

Traction

Evidence of pull—developers and enterprises standardizing on the product, daily-use stickiness, and conversion rates that beat traditional SaaS. For frontier companies, rapid progress and customer adoption stand in for revenue history.

“Thousands of developers and Fortune 500 companies have AI model choices to make every day and yet continue to standardize on Anthropic given its technical leadership.” — Tripling Down on Anthropic
“Within days, I was hooked—checking it multiple times a day with the same addiction I'd seen with the best consumer apps.” — Tim Tully
“AI buyer conversion rates reach 47%, nearly double traditional SaaS at 25%” — 2025: The State of Generative AI in the Enterprise

Team

Deeply technical founders—ideally repeat teams who have shipped hard systems together—whose backgrounds earn conviction fast. A best-in-class team is treated as the first moat.

“Zain is the kind of deeply technical founder who earns conviction fast.” — Menlo's Investment in Gimlet: The Multi-Silicon Inference Cloud
“This team built hard distributed systems together, shipped them to enterprise customers, and is choosing to do it again tackling an even more ambitious problem. That continuity is rare for such a talent-dense team.” — Tim Tully
“We're impressed with the many moats the company has built, starting with the best team in the industry.” — Matt Murphy
“Between the product's immediate utility and the exceptional backgrounds of Elias and his co-founder Luke, the investment decision became obvious.” — Tim Tully

Business model

An understanding of how value is captured—product-led growth motions, and where AI shifts pricing toward outcomes. They note PLG drives a far larger share of AI spend than traditional software.

“27% of AI application spend comes through product-led growth—4x the traditional software rate of 7%” — 2025: The State of Generative AI in the Enterprise
“Builders consistently choose frontier models over cheaper, faster alternatives. They prioritize and pay for performance.” — Tim Tully
“Agents sit as decision engines at the center of the control flow for an application, in contrast to the hard-coded logic of today's RPA bots.” — Beyond Bots: How AI Agents Are Driving the Next Wave of Enterprise Automation

Competition

Founders who know their industry cold—able to map the relevant players and articulate how their approach resembles or differs. They favor AI-native startups out-executing incumbents and durable moats beyond the model itself.

“You should be able to describe the relevant market players and how their approaches resemble or differ from yours. Conducting market mapping exercises like those developed by Steve Blank can be helpful for this.” — Refine Your Business Idea: Our Elevator Pitch for Future Founders
“AI startups captured 63% of application layer revenue versus incumbents' 37%” — 2025: The State of Generative AI in the Enterprise
“We're impressed with the many moats the company has built, starting with the best team in the industry.” — Matt Murphy

Why now

A crisp answer to why now is the right moment—grounded in a technology, behavior, or regulatory shift—ideally backed by industry data. They are explicit that timing kills startups that arrive too early or too late.

“Your pitch should highlight why now is the right time to tackle this problem. Industry data and statistics can be helpful in developing this point of view.” — Refine Your Business Idea: Our Elevator Pitch for Future Founders
“LLMs have finally made it possible to understand and act on unstructured customer data at scale.” — Tim Tully
“The shift from simple RAG pipelines to complex, multi-step agent architectures was creating a new class of infrastructure demand for a new compute substrate.” — Tim Tully

The ask

A pitch that is concise and conversational—they advise keeping the elevator pitch high-level (around 250 words) and iterating until it resonates. The ask is framed as inviting a partnership where Menlo commits more than capital.

“When we invest, we commit more than just capital. Through the ups and downs, we take the time to understand each company's unique needs” — Menlo Ventures | About Us
“More often than not, founders cycle through several pitches until they land on one that feels compelling.” — Michelle Aguinis

What Menlo Ventures rewards and penalizes

What excites Menlo Ventures

  • Deeply technical, repeat founding teams who have shipped hard systems together before
  • A problem stated with a unique insight and quantified, mis-allocated spend
  • Daily-use stickiness and developers/Fortune 500 standardizing on the product
  • A crisp, data-backed why-now tied to a real technology or behavior shift
  • Operating in a category where AI-native startups out-execute incumbents
  • Boundless market that can produce an iconic, world-changing company

Watch-outs for Menlo Ventures

  • A problem with no unique insight—just 'this is painful'
  • Vague or undefined target buyer/user
  • No coherent why-now, or timing that ignores industry data (too early or too late)
  • Inability to map competitors and articulate genuine differentiation
  • Over-detailed early-stage solution that should still be high-level and evolving

Who decides at Menlo Ventures

Matt Murphy — Partner
“We're impressed with the many moats the company has built, starting with the best team in the industry.”
Tim Tully — Partner
“This team built hard distributed systems together, shipped them to enterprise customers, and is choosing to do it again tackling an even more ambitious problem. That continuity is rare for such a talent-dense team.”
Michelle Aguinis — Menlo (author of the future-founders elevator-pitch framework)
“At the core of any successful business is a problem that needs to be solved. Your pitch should clearly define the problem and provide unique insights into why it matters.”
Mark Siegel — Managing Director
“We want to help create products and services that improve peoples' lives and disrupt or create enormous markets and result in iconic, world-changing companies.”

What Menlo Ventures actually backs

Where Menlo Ventures is thinking now

Menlo Ventures's published guidance

Benchmark your deck against Menlo Ventures →

PitchLens grades your deck slide-by-slide against Menlo Ventures's own published playbook, with a citation on every point.

← Browse all 124 VC firms · PitchLens home