Onix CEO On 5x AI Growth, GenAI Projects And Google Cloud Tech

'AI is basically like electricity or fire. It is that kind of fundamental technology which only our imagination can predict the growth of the AI market size,' says Onix CEO Sanjay Singh.

Onix is witnessing a 500 percent increase in its AI business and winning new customers who are demanding generative AI solutions as the all-star Google Cloud partner bets that AI will become a fundamental technology with unlimited potential.

“AI is basically like electricity or fire,” Onix CEO Sanjay Singh told CRN. “It is that kind of fundamental technology which only our imagination can predict the growth of the AI market size. It’s absolutely a massive opportunity.”

Onix is a 13-time Google Cloud Partner of the Year winner that has been focused on data and AI for years. The New York-based AI company has 75 AI customer projects in production—from transforming patient care to deploying AI in call centers to boosting agent productivity, as well as AI customers in retail, telecom and financial services industries.

“We’re helping customers with business transformation across the value chain, creating nonlinear growth models for customers,” said Singh. “We’re enabling new product introductions, new solutions, new manufacturing capabilities as well as breaking the linearity between cost and revenue.”

Onix: ‘Almost Every Customer’ Is Looking At AI Solutions

The value businesses of all shapes and sizes will get from implementing GenAI solutions alongside Google Cloud.

“Google is innovating at a very rapid pace. Let’s suppose there are multiple models deployed within the customer environment. That model also undergoes refresh all the time from Google. That is where a partner like us comes in, and we make sure that the model is giving the right results, you’re fine-tuning it, you’re making sure that the model is trained on the right data—that is where the MSP MLOps, DataOps and the AI Ops come into the picture. That is super critical and it’s a very high growth area for us,” said Singh. “Almost every customer we’re talking to is talking about this opportunity and problem.”

Onix is the ideal channel partner that Google Cloud is looking for: a next-generation AI-focused MSP that provides continuous lifecycle services of data and AI solutions.

“Our view of what AI models do is take every role in a company—marketers, customer services, salespeople, etc.—they now have a digital expert that can collaborate with them,” Google Cloud CEO Thomas Kurian told CRN. “A partner can build an entire business, a brand-new business, using AI models to do that.”

In an interview with CRN, Singh talks about Onix’s vision and strategy for generative AI as well as Google Cloud customer momentum.

What are some unique AI use cases that you see with potential game-changing business impacts?

This is a process that we follow across all industries, whether it be banking or healthcare, any business who wants to become closer to millennial customers. They want to use AI to transact because the new generation of customers are very tuned to technology-based interaction rather than in-person-based interactions like in a traditional bank.

Or a healthcare company which wants to improve patient care. Imagine if you go to a doctor’s office and the moment you check-in, your entire records are available to the doctor in a summarized manner. Your history is available to the doctor. If you’re speaking in Spanish language, the entire transcript is converted into your language of your choice. That’s the power of AI.

Another very interesting use case, which we did for an EV [electric vehicle] company... so we have developed a fleet management system for them.

This EV is used for important shipments of goods, products and services. It has to be highly reliable platform and very modular platform.

So it will have real time software engine performance and the entire platform performance. It will have real time location. It will tell you that this that car needs servicing and then it will automatically schedule a prescheduled maintenance using artificial intelligence and data location.

In the future, it will also have a profile of the delivery drivers. Here’s where the beauty comes in. It’s going to be a world without boundaries. The system will know that if I’m a delivery driver and I have back pain or a health issue, let’s suppose then the workload which is assigned to me is not the right workload for me to go and pick up. So it will not allocate you for that particular workload. It looks at somebody else.

In return, it will avoid potential claims and worker compensation issues in the future. It will enable those experienced services in the vehicle itself. You don’t need to use your phone for that. All of this is powered by Google Cloud and artificial intelligence, which we are deploying for this customer.

How many and what type of AI customer projects are you currently working on? What do businesses hope GenAI will accomplish?

In the last few months itself, we have in over 75 ongoing AI projects concurrent, across industries—whether it be transforming healthcare to transforming patient care, whether it be a medical assistant, whether be in the financial industry or in the retail industry—it’s across the spectrum.

The way I see AI with customers is in two very simple lens: either it is driving efficiencies—it is taking away what you do manually, it is taking what takes many days, it is taking what is humanly impossible to digest in a short period of time and becoming an assistant— it means driving operational efficiency.

Or, AI is driving innovation. It is giving you capabilities that didn’t exist before. It is helping you with business transformation across the value chain creating nonlinear growth models for customers in multiple dimensions. In dimensions of: enabling new product introductions, new solutions, new manufacturing capabilities as well as breaking the linearity between cost and revenue. Those are the kinds of use cases that we are that we are seeing.

This is just the tip of the iceberg.

Once all these initial experiments get into scale across the customer value chain, each and every process will be powered by AI. Again, each and every process.

Google Cloud’s CEO (Thomas Kurian, pictured) told me with AI, partners can sell more in every customer-facing department but also in the back office around things like accounts payable, help desks and general purchasing. Do you see an opportunity here?

It’s a very strong growth area for us. In the past month, I don’t know how many intelligent agent deals we have signed. These are all with large companies—Fortune 50 or Fortune 100 large companies.

This is all around call center artificial intelligence deployments in the call center, agent productivity area. The opportunity didn’t exist earlier and now it is becoming mainstream as customers want to use the first touch point with their customers very intelligently.

Such as to provide the agents with the tools and the solutions to predict churn; to predict who are their top customers; to work to be a true assisted in the agent journey. This goes across telcos, it goes across a financial company, it goes across healthcare companies, it goes across different dimensions.

Everybody who needs the customer service, the deployment of this AI tech is giving dramatic outcomes. Not small results, but dramatic improvements across cost, innovation and customer experience. This didn’t exist earlier.

How much has Onix grown its AI sales in 2023?

I would say at least 500 percent [growth] from Q1 to Q4 of 2023. So at least 5x.

I am putting all my investments in data and AI. All my new hires are in data and AI. My demand is outstripping supply in terms of data and AI capabilities. That’s the reason why we [acquired AI and data company Datametica in October] to support us on the on the data and AI journey using a automation-based model where we create platforms to do the Data-Ops, ML-Ops, making sure the language models are trained well on the right data sets within the customer’s environment, and making sure that it is contextual in nature—not only just transactional in nature.

For example, you are a retail customer. Your data exists in multiple systems. … But I need to form a 360-degree opinion of you. That’s what our platform does from a contextual perspective—managing the models to make sure it is giving the right outputs and inputs and managing that for the for the customer lifecycle.

MSPs are only one part of the answer. The other part of the answer is data transformation and curation. You curate the right type of data on which you want your AI models to work. That is extremely important.

Not many people understand how to unlock the value of AI in the customer environment. This is where we and Google partner together to unlock the value together.