1Mby1M Virtual Accelerator AI Investor Forum: Sandeep Sardana, BluePointe Ventures (Part 2)

Sramana Mitra: So, is vertical AI your primary investment thesis?

Sandeep Sardana: It is. Vertical AI is a natural transition from vertical SaaS. The business models are evolving again. In SaaS, we had a recurring revenue model, but in vertical AI, much is shifting to outcome-based models. Many services are being layered in, which may or may not be recurring. Business model changes are happening simultaneously.

The time to value is where we see a big shift. The ROI customers expect—and how quickly they want to see it—is changing. Customers now expect benefits much sooner, sometimes within days or even hours. You can deploy solutions and start using them immediately to improve processes, workflows, and data management.

Sramana Mitra: Interesting. There’s a range of things you’ve mentioned. Let’s explore them to get a clearer understanding of your perspective on vertical AI. You come from vertical SaaS and have a portfolio of such companies. Is vertical AI being retrofitted into those companies? And if so, how successful has that been? Are AI-native companies at an advantage in vertical AI?

Sandeep Sardana: Yes and no. I’m seeing both, and time will tell which strategy wins. Distribution is a major advantage for companies that already have it. If they can solve the AI challenge while maintaining their vertical SaaS business, they benefit from existing customer trust and procurement relationships. They’ve already crossed hurdles like security and vendor approval, so now it’s about leveraging AI.

Teams are capable of integrating AI—sometimes through bots, redefined workflows, or computer vision—depending on the case. We invest in vertical SaaS companies that build industry-specific assets.

For example, we have a company called Tekion. Tekion focuses on automotive retail and integrated 14 different dealership software packages into a single platform. They connect manufacturers, dealers, and customers in one system. For them, adding AI isn’t difficult since they know where it can help—whether in finance, customer service, or recognizing when a car is in the service bay.

Some companies can leverage AI quickly, while others may struggle. New startups will emerge and disrupt incumbents. There are also entirely new use cases that didn’t exist before. For example, AI-driven code generation appeared suddenly and showed that AI can write high-quality code.

Sramana Mitra: Vibe coding, I think, is a different issue. We can talk about that in a moment, but let me first comment on what you said. In vertical SaaS that is already well deployed—like Tekion’s automotive dealership platform—moving from vertical SaaS to vertical AI has a clear path. There’s a lot of workflow, and in these cases, agentic AI is a viable architectural path to automate processes and add agentic functionality. This transition is best done by people who have domain knowledge and are already deeply embedded in the workflows of that industry.

Sandeep Sardana: That’s correct. They have access to proprietary data, they understand the language, and they have the data. Many of these industries that were digitized through vertical SaaS were traditionally slow-moving or on-premises. We helped lift them into the cloud. Once you bring them into modern infrastructure, it becomes much easier to add agentic AI components to workflows and processes.

When you’re already a domain expert with established distribution and customer trust, you’re well positioned to take the next step forward with AI.

Sramana Mitra: I think the ones that are having difficulty retrofitting are those with architectural limitations in their existing systems.

Sandeep Sardana: A hundred percent. You’re absolutely right.

This segment is part 2 in the series : 1Mby1M Virtual Accelerator AI Investor Forum: Sandeep Sardana, BluePointe Ventures
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