The latest from 8VC
Ask anyone who’s ever begun a term paper the night before it’s due: there are stark tradeoffs between research time and research quality. This is especially true of primary user research, one of the fundamental ways large enterprises can ensure their products resonate with customers. Historically, this has required a choice between user interviews, which are high-fidelity but slow, manual, and expensive, and surveys, which are scalable, cheaper, and faster, but often result in unrefined, low-signal data. Although there have been some strong companies on the survey side, e.g. Qualtrics and Medallia, this uneasy compromise has always persisted—until now.
Outset has harnessed recent gains in frontier models to pioneer a new primitive: an AI-moderated 1:1 interview with the speed and scalability of surveys and the richness and detail of traditional interviews, enabling any company to become more customer-obsessed. Outset’s platform allows researchers to easily set up interview guides, employ agentic video interviews and usability testing, and recruit subjects through panel integrations or their own user bases. They can then conduct multilingual interviews in any modality: video, voice, text, or usability. Outset’s analytics suite is the most robust available, providing research teams with instant, customized quantitative reporting, as opposed to the simplistic, ChatGPT-style outputs typical of competitors.
AI models are finally capable of transforming research, but implementation is still critical. Outset completes the equation by handling the last mile of delivery for customer-specific tasks and use cases, building on the founders’ domain experience. CEO Aaron Cannon is intimately familiar with user research, from his time as a research consultant working with Fortune 500s to roles as VP of product and design at several high-growth startups. The result is a complete offering for the core workflows of both UX research and market research, from input guides, to interviews, to how they surface insights. With substantially more data-gathering power than traditional qualitative methods, Outset represents an intriguing longer-term opportunity to consolidate enterprise customer knowledge.
Along with a robust enterprise toolkit, Outset’s platform is designed to meet the requirements of even the largest companies, with industry-standard security, compliance, access controls, and fine-grained data segregation. Existing customers include category leaders ranging from Microsoft and Nestle to WeightWatchers, Away, and Hubspot. Outset’s revenue has doubled over the past four months, while per-customer usage has quadrupled over the past year.
Outset’s founding team helps to set them apart from their closest competitors, and is a major reason behind our investment. Aaron’s product chops and exceptional user empathy are well complemented by co-founder and CTO Michael Hess, a firefighter turned engineer with a rare gift for velocity. Michael also started Watch Duty, a vital resource for wildfire tracking that recently became Apple’s most-downloaded free app. Their chemistry is helping to capitalize on incredible market pull, just as the ability of AI to scale and enhance expertise-driven services hits increasingly higher gears.
User research is about the power of human insight, and in their elegant application of AI, Outset is helping the field to become more human-centered than ever. We’re proud to lead Outset’s newly announced $17 million Series A, and support them in making qualitative insight scalable and tangible.
Announcing Our Investment in Outset
Ask anyone who’s ever begun a term paper the night before it’s due: there are stark tradeoffs between research time and research quality. This is especially true of primary user research, one of the fundamental ways large enterprises can ensure their products resonate with customers. Historically, this has required a choice between user interviews, which are high-fidelity but slow, manual, and expensive, and surveys, which are scalable, cheaper, and faster, but often result in unrefined, low-signal data. Although there have been some strong companies on the survey side, e.g. Qualtrics and Medallia, this uneasy compromise has always persisted—until now.

Announcing Our Investment in Outset


Drew Oetting On Building An $8 Billion Venture Capital Firm To Invest In Startups That Are Fixing Our Broken World
Drew Oetting is one of the biggest forces providing the financial fuel this new generation of fast-growing, super-sized startups need to make it. His venture capital firm, 8VC, has invested in startups like Unlearn, Chaos, Tome, and Ushur.
Charles Srisuwananukorn (Together AI) Fireside Chat
We were thrilled to feature Charles Srisuwananukorn from Together AI at January’s Chat8VC. Charles is the Founding Vice President of Engineering at Together AI, where he leads the company’s work on AI infrastructure and clusters. Previously, he was Head of Applied Machine Learning at Snorkel AI and held engineering roles at Apple. He studied Computer Science at Stanford and has helped steer Together from an early contributor to open-source AI to a full-stack infra platform.
Joe Chen and Jonathan Shen (Upwork) Fireside Chat
We were thrilled to feature Joe and Jonathan from Upwork at March's Chat8VC in San Francisco. We covered their journey from teams like Google Brain and Cruise, and their own startup, to leading AI efforts at Upwork—building Uma, a suite of specialized LLMs powering workflows for freelancers and clients across the platform.
Clear Eyes, Fuzzy Joins, Can’t Lose: Announcing Our Investment in Structify
Human-quality workflows need human-quality data, an axiom that has only grown truer in the AI-first enterprise. However, access to complete, high-signal data remains a limiting factor, given steep data provider fees, inflexible schemas, AI hallucinations, and scattered, inconsistent, and mutating sources. Customers don’t need to be data scientists to recognize shovel-ready datasets, but if they need to be data scientists to generate them reliably, data will always be rate-limiting.
Quantifying the Impact of GenAI Developer Tools
It’s widely agreed that GenAI will transform software development, and GenAI dev tools have emerged as cornerstones of 8VC’s portfolio and broader AI productivity thesis. Up to now, however, hard data on the scale and specifics of this shift have been missing from the equation. In competitive industries, the speed and efficiency gains promised by GenAI coding tools could well mean the difference between market leadership and obsolescence. Companies can’t afford to select the wrong tools and end up on the wrong side of the AI adoption curve.