Thought Leaders in Artificial Intelligence: Antuit Co-CEO Sivakumar Lakshmanan (Part 3)

Sramana Mitra: We’ve talked about the use case and data signals. When you started, how did you get the data with which to train the model, and what was the seeding of the algorithm?

Sivakumar Lakshmanan: We are single-tenant. We don’t train our models on one customer and use them for other customers because of the sensitivities involved in retail sales data and consumer product sales data. We train the model on our customer’s information. The seeding happens for individual customers and not on the industry.

Sramana Mitra: Let’s say your first ever customer, why did they let you do that? What did you bring into the process or how did you convince your customer to do that?

Sivakumar Lakshmanan: Companies take different journeys into being AI SaaS companies. We started as a services company that helped customers solve individual custom use cases. As we gathered momentum, knowledge, and credibility, we got brand permission for folks to buy our product.

You are talking about decisions that are highly influential. Today, we decide 90% of the stock that goes into US supermarkets for bread. You cannot just say you have the best product; you have to build it over time. We took the services route to build credibility.

Sramana Mitra: We are very big fans of bootstrapping using services. We have a whole methodology around that. What did you have on your team to convince these large enterprises to bring you in as a service provider?

Sivakumar Lakshmanan: When you are solving these problems, you tend to solve global hunger. One day, you solve a pricing problem. Then next day, you solve a forecasting problem. You keep moving and you are not building credibility in one area.

The key here is to stick to the course. It is not easy. You cannot chase those specific opportunities in the beginning. You need to pick your battles and your expertise. When we started, the team came from different domains that had a certain credibility. You need to stick to those areas and do that multiple times. After some point, you will become a natural choice for solving those kinds of problems. The narrower the problem you are solving, the better. 

Sramana Mitra: You hit the nail on the head when you said to pick one problem and solve that over and over again. The path to productization is by solving a single problem. 

Sivakumar Lakshmanan: Yes, the initial few years will be a struggle. It’s hard to say no.

Sramana Mitra: Not only that, but it’s also hard to acquire customers. New customers are harder to acquire. Once you have a customer, the customer will give you all kinds of problems to solve. You already have the relationship. It’s easier to go within the customer and make a lot of money from that customer by solving many problems. That’s why services companies don’t productize usually.

Sivakumar Lakshmanan: Exactly right. 

Sramana Mitra: If your goal is to remain an AI services company, you can take one customer and upsell and cross-sell. If you want to productize, you need to solve one problem for many customers and build a reputation around that. Those are two different strategies. It’s a very interesting discussion for people on options. Forks on the path essentially.

Put on your industry thought leader hat. From your vantage point, what are some of those problems that customers are asking for solutions to that you have chosen not to solve, but you know that those problems exist?

Sivakumar Lakshmanan: There are a variety of problems to be solved. The problems are also changing rapidly. One of the areas that are very big on our customers’ minds is doing more with less. How do I execute my plan and then grow at the pace I want and then do that with the resources that I have?

That has a sustainability and profitability angle to it. Surprisingly, they go together in this case. How can I be more intelligent? How can I reduce the waste? This is a broad set of problems. Grow without compromising efficiency. We solve some parts of it. There is a variety of areas within this that needs a solution.

Sramana Mitra: Can you double-click on that and give some examples?

Sivakumar Lakshmanan: A diagonal area is a circular economy with zero waste. This is a problem that needs a solution with AI. Is there a way to execute CPG and retail value chain without waste? Is it intelligent packaging? Is it a closed-loop system? There is data involved. There is a business model innovation involved. Everyone is looking at it now. Now, it’s scattered. That will be a trend. 

Sramana Mitra: You did bootstrapping using services? Are you completely bootstrapped or have you raised money?

Sivakumar Lakshmanan: No, we are backed by Goldman. Our geographical expansion was funded by Goldman Sachs.

Sramana Mitra: How many years did you bootstrap using services before bringing funding in?

Sivakumar Lakshmanan: We did that for two years. Then we brought Goldman and other investors in. We’ve always been funded from the beginning. We had a seed fund.

Sramana Mitra: Thank you for your time.

This segment is part 3 in the series : Thought Leaders in Artificial Intelligence: Antuit Co-CEO Sivakumar Lakshmanan
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