The following interview was conducted by Sacra—May, 2022

Thilo is the co-founder and CTO of Levity. We spoke to Thilo about how businesses can use AI to automate workflows, the hard part about building an AI tool in the cloud, and competitive dynamics in the workflow automation market.

1. Can you tell us a little about Levity? What is the problem that Levity is trying to solve?

2. Can you talk about your core customer profiles and some of your key use cases?

3. What are your thoughts on the workflow automation space and how it’s evolved? What does the future look like?

4. Where do AI-based tools like Levity and others fit in in this market? Do you see them as replacing existing tools or as complementing and extending the value chain?

5. Do you see breakpoints where customers duct-tape together their own solutions with existing automation tools and eventually graduate to something which is automated or AI-based like Levity?

6. How does Levity actually work? What are the various components that come together from an AI and data model point of view?

7. Can you double-click on how your customers are currently importing their data? You mentioned import integrations. Is it self-serve or do they reach out to you?

8. What is the real hard thing about what you are building right now that many people who are not trained to understand AI will not really appreciate?

9. How do you optimize infrastructure and manage operational costs? As you scale, how different will your infrastructure look—will this grow by 10X or 100X?

10. With regards to the modeling and the data needed to train it, what happens if the data is not sanitized? What are the steps you share with your customers or take on their behalf to make it more consumable by the AI engine? Have there been issues with the quality of data used?

11. Are there any trade-offs between using a no-code tool versus developing something like this in-house? Are there situations where one fares better than the other on cost or performance parameters?

12. From a customer retention point of view, what are some of the things which make Levity more sticky?

13. The no-code market is full of solutions that deep dive into specific vertical use cases—revenue operations, fraud detection, revenue forecasting, and so on. What went into that decision to build Levity as a horizontal solution?

14. Many SaaS or cloud-based companies offer a freemium tier or free trials. Levity starts with a paid plan as its lowest tier. What was the thinking there?

15. Levity 1.0 essentially is about data categorization, tagging, and labeling. What's your vision for Levity 2.0 and beyond?

16. In terms of your tech, vision, and product, what will Levity look like five years from now?On the meta level, we solve input problems around unstructured data coming from third parties and we cover the whole value chain end-to-end, from raw historical data to fully-integrated solution without any developer involvement.