Scale Venture Partners

Congratulations to the Spot AI team on their launch of Video AI Agents! Instead of "going to the tape" to see what happened after the fact, these agents work as an extra set of eyes to make workplaces safer, more efficient, and more secure. This is a huge step forward, transforming passive video surveillance into a proactive problem solver.

Having made our first investment in intelligent apps in 2015, Scale is nearly ten years into AI investing. In conversation with Crunchbase's Gené Teare, Scale Partner Rory O'Driscoll cuts through the post-ChatGPT hype to break down AI's impact on the market into three waves. From BILL, Box, and WalkMe™ to his most recent investments in applied AI startups Tavus and Klarity, Rory has been on the ground floor of investing in numerous technology shifts. Read more on how he sees this third wave of AI investment playing out. https://lnkd.in/gncjQfcw

Congratulations to the Fixify team on their raise! Fixify has revolutionized the helpdesk with a solution that is perfect blend of technology and human expertise. Their automation, powered by the latest in AI, can handle a majority of support tasks. Where automation reaches its limits, skilled professionals from Fixify’s team step in. We're excited to be part of Fixify's journey. Read more from TechCrunch and the Fixify team below.

Congratulations to honeycomb.io on the launch of Honeycomb Log Analytics and the Honeycomb Telemetry Pipeline! This launch enables the ingestion of any data type–including logs–into Honeycomb’s high-cardinality datastore and query engine. Honeycomb created modern observability. With Honeycomb, engineering teams can manage and analyze log data with speed, efficiency, and confidence, transforming observability from a cost center to a value driver. Check it out: https://go.hny.co/3BMkQys

We're excited to announce our investment in Galileo 🔭 AI is transforming the enterprise. But, the absence of effective evaluation and observability methods to measure the quality and trustworthiness of these new systems at scale poses a significant barrier to deployment. If you cannot evaluate the output of a language model, how will you test an application powered by one? And if you cannot test an application, how do you expect to deploy it in the first place? Enter Galileo. Galileo offers a comprehensive suite of tools for AI debugging and observability, enabling AI engineers and stakeholders to gain visibility into the performance of their AI models. By providing not only customizable evaluation functionality, but also error analysis and tracing, Galileo goes beyond bare bones evaluation and enables customers to understand not just if their models are wrong, but why they are wrong and how to fix them. Congratulations to the team!

Join us with Eric Anderson (Partner, Scale Venture Partners) and Thomas Kirk (Principal Solutions Architect, Permit.io) as we explore the surprising ratio between getting an MVP ready and reaching full maturity. We also dive into the challenges of cloud spot pricing and how unpredictable it can be for customers. Then, we look at the intriguing world of chaos engineering, where companies purposely break their systems to build stronger infrastructure. Episode 25 is now live! 🔴

Even with a tightly defined Ideal Customer Profile (ICP), many companies struggle to select the right target accounts to pursue and prioritize as they move into enterprise. As a result, they waste time and effort targeting the wrong—and often, too many—prospects. For our series How We Scaled This, Sydney Sloan walks through her four step approach to address this problem, from defining the ICP to engaging accounts.

In case you missed it—AI Infrastructure goes for a premium. But comparing these market dynamics to historical trends might give you some pause. Went through these topics in our latest: https://lnkd.in/ghx_cTcz

🚨 A former product manager at Amazon and Google, Eric Anderson leads AI, cloud infrastructure and security investments at Scale Venture Partners. He joins us for VC Wednesdays. 🚨 ✒️ How would you describe your investment thesis? I look for tools for technical builders — things that product managers, software engineers, data engineers and mechanical and hardware engineers can use. Part of the reason is that individual users have become more empowered than ever before. Historically, IT has chosen tooling, but nowadays, tools are getting democratized and individual developers can now be in the driving seat. How I measure that in an investment is: Is there a value prop for the individual and the organization? For individuals, the value prop could be productivity or a better user experience, whereas for the organization manager, it could be cost savings, for example. ✒️ What’s a recent investment that meets this criteria? We just announced an investment in Cortex, which is a service catalog for engineers. Individual developers love it because it's like a homepage for when they need to go find a service or contact a service owner. But more importantly, organizations love it because it allows for better change management. Let’s say you want to have everyone upgrade to the latest version of Java; you can easily track which half have done it and which haven't. There's now a mechanism to introduce change in the organization that doesn’t entail spreadsheets. ✒️ Where does AI fit into your thesis? I'm really excited about AI agents — by which I mean a bundle of AI automation that’s analogous to a job role. So, we recently invested in the company QA Wolf for example, which is like a quality assurance engineer in a box and has 40 microservices inside of it. It could represent a new kind of platform-as-a-service paradigm, but instead of building microservices or containers, you're building agents. ✒️ You’re a proponent of open-source projects. Does that also extend into AI? It’s likely that we’ll have a proprietary and an open-source winner, like Windows and Linux or a Snowflake and a Databricks. There will be an OpenAI that serves the security-conscious people who don't want to build things themselves, and a Llama that will overtake most use cases, where developers get to choose and have a little more customization. I'm hesitant to bet on anything in between, like engineering-specific foundation models, including poolside. ✒️ What’s one investment that you regret passing on? Snyk. We were the first in line for their Series B, and it was the prototypical deal I look for — it had developer love, a top-down  mandate that made sense and growth metrics. But there was a timing element, where I was preoccupied with something else and had questions about how big the problem they were trying to solve was. I ended up overthinking it, but Snyk would have been a slam dunk. #VCWednesdays #vc #venturecapital #startups #TechonLinkedIn