Thought Leaders in Artificial Intelligence: Antuit Co-CEO Sivakumar Lakshmanan (Part 1)

Siva has bootstrapped an AI SaaS company with Services. He shares invaluable insights on accessing data for building AI models and product strategy choices the company has made.

Sramana Mitra: Let’s start by having you introduce yourself to our audience as well as to Antuit.

Sivakumar Lakshmanan: I am the Co-CEO at Antuit. Antuit is an AI-as-a-Service company that targets retail and consumer products. Our goal is to make the supply chain and the merchandising process in retail and consumer products more intelligent. For the decisions around demand, what price do you sell, and how do you shape the demand, we leverage artificial intelligence to drive these decisions.

Sramana Mitra: Can you pick three use cases and deep dive into each of them? Explain the data infrastructure and signals that you need.

Sivakumar Lakshmanan: The first one is AI forecasting. It’s the process of identifying what your future-looking customer demand is. It could be demand for short or long term. Typically, you’d need this ability in retail forecasting. If you are making decisions on manufacturing and you happen to be a retailer who has sourcing in Asia, you’re typically making decisions 12 months in advance.

If you’re a consumer product company with local manufacturing, you’re making that 12 weeks. The medium to long-term demand is important. There is also a short-term version of the demand. There is also a short-term version of the demand which is important on how you deploy inventory to the stores and customers. We work across the time horizon. In terms of data, these are machine learning models that are continuously learning.

Typically, you will chart with historical data, trends, and seasonality. You can go as low as to individual product level or to a regional level. Historical sales and the pattern of the demand is very important. Oftentimes, history may or may not be a true representation of the future. It is becoming common that history is not in the presentation of the future.

Naturally, other information becomes critical. If you are a drug retailer and you are tracking the flu trend, do I need to stock a lot of cold and flu medication? What is the allergy trend this year? If you are a consumer product company and are selling food and beverage, you need to be aware of when are the ship coupons coming out. When is the back-to-school? All those external information becomes super helpful.

Even internally, companies do a lot of work to shape their demand. Shaping the demand is, you are running a marketing campaign and spending a lot on advertising. Those will influence your demand. You will be running promotions. You will see a display in a Walmart. You walk by and then you pick one. You may or may not need the product. You’re driving the trade promotion at the retailer that is driving demand. That becomes an important input.

Your advertisement, marketing, and promotion spends act as very important inputs. Your external data is a very important input. For instance, let us take Starbucks. If you know that there is going to be a parade, that affects your stocking. 

This segment is part 1 in the series : Thought Leaders in Artificial Intelligence: Antuit Co-CEO Sivakumar Lakshmanan
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