Robotics, ERP and aerospace: the resume of Vaibhav Vohra, CPTO and EVP for Epicor, is a varied one. Vohra joined Epicor in 2021 as its chief product officer and SVP, coming from previous VP product roles for robotics companies in the San Francisco Bay Area. In 2023, he became the company’s CTO in addition to chief product officer, a role in which he has led the vision between Epicor and AI technology for the enterprise market.
Prior to robotics, the executive was a VP for SAP, again heading the product realm as the German company made its SaaS transition during the 2010s. Ideal experience, one might say, for Epicor, a fellow ERP vendor which has been making its own cloud journey under the tenure of CEO Steve Murphy.
When talking about Vohra, Murphy tells me that sometimes geniuses have a “hard time” breaking out from an intellectual mentality to deal with people and understand their customers.
“[But] Vaibhav is the rare genius who in addition to the very high intellect, is able to understand customer needs and […] when it comes to human beings, their wants and desires and their need to feel connection, satisfaction about what they do.”
Murphy tells me this in Epicor’s Dublin, California base, on a day ERP Today spoke with both the company’s CEO and CTO. Meeting the latter, Murphy’s description makes sense, with the technologist straddling both worlds of technology concepts and customer needs with aplomb.
A good example is when Vaibhav Vohra is asked about the history of Epicor and AI and what’s changed in the years from inception leading up to the current boom in Generative AI, alternatively known as GenAI. Fittingly, Vohra talks as both CTO and CPO, underlining how AI has changed to be about “empowering workers so they can make more valuable decisions” in their day to day – the frontline staff in the manufacturing and distribution industries which Epicor tailors to.
Epicor and AI
As detailed in our previous interview with Steve Murphy, Epicor formed out of the financial and accounting software vendor Platinum Software Corporation, which was founded in its headquarters-to-date of Austin, Texas. Platinum had started developing manufacturer-specific software packages in 1998, and by 2005 Epicor was offering what it called the industry’s first manufacturing solution based on a completely service-oriented architecture.
2011 saw Epicor merge with Activant, a leader in supply chain connectivity and the automotive market. In 1984, the California-headquartered company had brought its electronic parts catalog from print to digital. Listing over 8.8 million automobile parts from engine to exhaust, Activant’s Automotive Electronic Catalog was one of the first digital inventories out there, if not the world’s first for the US automotive sector.
From print to digital, Epicor likewise transformed from on-prem to cloud, and became, in Vohra’s words, the first ERP vendor to build an iPaaS into its platform. Today, under Vohra’s leadership, Epicor is steering from cloud to AI. Another way of putting this is from “cloud to Cognitive”, in a nod to the company’s vision of “Cognitive ERP”, a symbiosis between AI and ERP that aims to redefine processes and operations in the supply chain for its manufacturing-heavy customer base.
Talking on the history behind current and past iterations of Epicor and AI technology, the executive notes the company has been working on artificial intelligence for around 40 years, to a half century. Tied in with this was the nascent thinking about the cloud, where cabinets of hardware could be removed to leave workers focusing more on the things that matter.
Vohra sees the SaaS transformation in ERP as the first phase, a perfunctory step where on-premises software gave way to cloud. Not enabled were capabilities coming through now to users such as those said to be possible with GenAI.
“So I think we’re now in the ‘Phase Two’ where SaaS really delivers on its promise of empowering people,” says the EVP, noting that the “numerous cabinets and tangles of messy wires” of yore were eventually replaced by ERPs connecting to a just-as-disordered collection of applications and processes.
For Vaibhav, the mission behind Epicor and AI software is “empowering essential workers with superpowers to give them ten times the skills and insights.”
He continues, “What I mean by that is for AI or any advanced technology to be successful, it has to be ten times better than whatever the human does, right? Essentially AI is going to cost more money. The value will not totally be delivered because of this, so you have to invest far more than you ever think.”
The CTO sees three elements of Epicor’s Cognitive ERP journey, starting with “Handshakes” to redefine how humans and machines talk to each other. For example, an agent can not only answer questions, but also check if its answer is as informative to the degree needed. It could also check context, pointing out to a user that a question may not be relevant and that something else should be asked instead.
Prism, Epicor’s GenAI service, also offers a code assistant to create automated business processes more quickly. There are also tools to automate supplier communications to speed purchasing, enabling users to automatically send Request for quotes (RFQs) to their supplier network, and sift quotes to determine the best price and fastest delivery.
Next are the “Gears”, essentially low-code tools which make automation and insightful analytics possible on the shop floor. These can be found in the Grow AI offering, helping users to generate, analyze, and act on multiple forecasts related to inventory, demand, and sales (an example of the latter are product suggestions based on past order history).
Finally from Epicor, we find the “Sparks”, which Vohra dubs insights to the power of ten. An example is given of one Epicor customer, Visa Cash App RB Formula One Team, based in Faenza, Italy.
“So we have an AI that actually allows [Visa Cash App RB] to send through all their suppliers and come up with the right trade-offs,” says the EVP. “And then gives you the insight to say ‘you should use this supplier.’”
Epicor is used to track in real time approximately 14,000 components, so the team will know when they need to make or buy a part. When the make or buy decision happens, Epicor Prism allows the team to quickly determine the best vendor to deliver the part at the right price, the fastest, and if that beats the time/cost of making it themselves, they buy it from that vendor.
In other words, the catalog from 1984 has come a long way, souped up and raring to go in a post-pandemic world. The CTO goes on to explain how Sparks are industry-specific insights powered by AI.
“It could be not just that example of supplier insight, but also a product recommendation for your customer. Steve mentioned turning a system of records into a system of actions – those are the Sparks,” explains Vohra.
The CTO also elaborates on the Gears element of Epicor’s cognitive ERP, which can help end users learn ERP faster. Citing the forecast that four million jobs are going to be created in US manufacturing by 2030, he notes that 50 percent are estimated to go unfilled due to skills shortages.
“It can take someone a year to two to learn ERP. What if we could bring it down? The Gears are meant to create this easy way to level up through an ERP system,” he says.
It’s an alluring proposition, especially when one considers the rise of AI comes with an increasingly apparent skills shortage, whatever the sector. ERP’s role is a crucial part of this discussion, for as the Epicor leader states: “ERP is the vehicle for AI, right. But AI is only as good as the data.”
Vohra believes Epicor has “the world’s best data” from first-party systems. It’s already on hand through what’s collected in the Epicor ERP, from the shop floor, through to suppliers’ shipping data, commerce data and more.
“These are all things that live in ERP. So by definition ERP companies have the best chance at succeeding at driving significant value with AI. So the more industry specific the better, which is why we feel like we have an unfair advantage.”
ERP Today is reminded that AI models are not one-size-fits-all, as you cannot apply the same model to different sectors. A competitive edge comes from the Make, Move, Sell economy. The data ERP ontology for manufacturing comes from part sub-assembly order, while for distribution it’s quote-to-order, via Epicor’s integrated development environment (IDE).
The technologist sees a level of parallelism between Make, Move, Sell, as reflected within the data model itself. This means when building AI, it’s possible to create a corollary to a use case in manufacturing, to distribution and also to building supply.
“It would be very hard to create that corollary [with other sectors]. It’s just such an orthogonal industry. So I’d say that that’s our competitive edge in the application of our AI.”
Makers, Movers and Sellers blend together as sectors, the EVP continues, instead of making for three distinct verticals. Some companies both make and sell products, for example.
“Everyone has to do some form of payments. Everyone has to make some sort of supply chain decision. Many have a last mile delivery […] When we’re more focused on it as an aggregate, we can then allow our AI agents to kind of cross over to various products.”
Those AI agents are brought up a lot by Vaibhav Vohra, and in a context that underlines Murphy’s view that the technologist can see beyond the tech and understand the human element driving baseline customer decisions and user operations.
With his background in robotics Vohra notes that where robots were seen as possibly replacing human workers, instead it turned out more skills and technical labor were needed to deal when a robot was introduced into “the wild” of a workspace.
As such, he believes that the idea that putting robots and AI into something means less humans are needed is “absolutely false”.
“When people found that they could use this as a superpower of augmenting what a human could do, that’s when most retailers, manufacturers, and distributors are more successful.”
With robotics, ERP, aerospace and now superhumans in the mix, it seems the skill set of Vaibhav Vohra has leveled up once again, much like the AI evolving behind ERP on an unstoppable trajectory.
