To gain the edge over the competition, enterprises are increasingly leveraging AI applications to help with their business functions and infrastructure management. Helping such enterprises with the development and deployment of AI projects is an Indian AI SaaS startup – CellStrat. The startup provides AI solutions and products to AI customers globally. CellStrat Hub platform allows thousands of global AI teams and developers to learn, develop and launch AI quickly and efficiently (AI Developer Tools and AI APIs on the Cloud). They are doing cutting-edge research in advanced AI domains such as Computer Vision, NLP, Reinforcement Learning, Graph Networks, Artificial General Intelligence, etc., and operationalizing these projects as AI SAAS services on the Cloud. CellStrat is backed up by a team of 250+ AI Scientists and a 15,000+ strong AI community globally. CellStrat targets domains such as InsureTech, e-commerce, automotive, and media, as there is a huge amount of data and CellStrat can help solve the problem by segregating them.
We had the opportunity to interact with Mr. Vishal Singhal, Co-Founder of CellStrat, who talked about how CellStart is serving global AI customers via an innovative AI SAAS platform and shed the light on how CellStrat reduces time to develop by almost 40-50% and leads to cost savings by almost 30-40%.
Here’s the excerpt from the interaction:
How CellStrat’s No-code Low-code strategy helps the AI developers and enterprises?
AI deployment has been a difficult and complicated task for a lot of users. By using CellStrat’s No-code Low-code strategy AI developers and enterprises can deploy AI Models as it is a cost-effective, simple, highly flexible, and customizable platform. It can be called from anywhere, including a web application, server-side application and edge devices in the near future. Our company has provided the existing APIs for developers to use at no cost and developing private APIs for enterprises that don’t have developers for the same.
What does CellStrat’s POC (Proof of Concept) do and how do the solutions help enterprises?
CellStrat will utilize the raw data from enterprises to prepare a POC (Proof of Concept). Once the POC reaches a desired minimum level of accuracy to the subject, CellStrat will start the billing on the SaaS model for the company. It facilitates enterprises to focus on their core business while the hard task of putting data to use is handled by AI API.
What are the reason and ideas behind your company choosing an AI SaaS platform?
Artificial Intelligence development, management, and maintenance take huge costs both in terms of manpower and cloud. It is unaffordable for most SMBs and many large organizations too, while the AI SaaS platform is able to distribute the costs across customers while removing the hassle of the above three. It becomes easy for customers to pay only for services they use. When affordability and flexibility become easy more organizations prefer getting AI SaaS services, hence CellStrat preferred the AI SaaS platform.
What do you think will be the impact on the workforce after adopting AI?
Artificial intelligence is becoming more widely recognized as a key strategic imperative for businesses. For many businesses, AI will be a game-changer, not just in terms of how they run their business processes or sell their products and services. It will create a completely new work environment in which jobs, businesses, and enterprises will grow, or change resulting in a complete transformation of the working culture. The streamlining of information and operations will better the work environment and the productivity along with the quality of output companies are able to provide, hence AI adoption will ensure a positive impact on any company’s functioning.
State some current targets and business strategies your company is planning on for 2022.
Data is the oil for artificial intelligence to work. Without data, such systems cannot be created or used. Thus, all areas of an enterprise that have huge data pipelines are targets for CellStrat. We have seen most data exists in finance, marketing, retail (both online and offline), media, manufacturing, and supply chain areas so these are our sweat spots while we are not closing options for other areas too as they come.
Using CellStrat’s AI platform for data analysis, what problems have you countered and resolved.
We at CellStrat, are currently optimizing revenue and increasing referral lead generation for media sites. We have increased average order value for e-commerce companies while decreasing customer churn and increasing end-customer purchase frequency. Forecasting inventory is now possible at both the stock-keeping unit and brand levels. We are increasing user sessions on EdTech sites. We are quantifying insurance claims for a few retail asset classes for an insure-tech company. These are only some of the problem statements we are currently working on among many others.
