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The Age of Enterprise AI

C3 AI president and CTO Ed Abbo and CTO of products Nikhil Krishnan discuss how generative AI can fundamentally change how personnel access and activate enterprise data.

Generative AI, a new set of artificial intelligence and machine learning algorithms that allows for the creation of new content from existing data, is taking the consumer and business worlds by storm. And its adoption is anticipated to rapidly ramp up, with the generative AI market projected to reach $110.8 billion by 2030. For individuals, the use cases for the technology span from creative to recreational to practical, while for enterprises, properly and responsibly deployed generative AI has the potential to increase efficiencies, reduce costs, and boost profitability. Tom Siebel, chairman and CEO of leading enterprise AI software provider C3 AI, believes generative AI is a technological breakthrough on par with the internet and the smartphone—and since 2020, his team has been building on the company’s 14 years of enterprise AI research and development (R&D) and industry-leading AI platform to capitalize on this breakthrough and bring it directly to customers. We sat down with C3 AI’s president and chief technology officer (CTO) Ed Abbo and Nikhil Krishnan, the firm’s CTO of products, who have been instrumental in developing the C3 Generative AI Suite, which was released to the public this spring. We spoke to Abbo and Krishnan about the challenges that come with enterprise data operations and how the C3 Generative AI Suite is designed to not only address these problems head-on, but to also revolutionize the ability for users to access and interact with information across an organization.

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Transforming enterprise data operations with generative AI

What are the biggest challenges facing today’s enterprises when it comes to information?

Ed Abbo: Most organizations have hundreds or thousands of systems with data spread across them. Large-size organizations may have more than 10,000 systems in some cases, so it can be difficult for users to find the information they are looking for across the enterprise. Efforts to assemble all the data from these systems into what are referred to as “data lakes” have not helped because, while the data might be in a single location, it is not unified. For example, if you work at a manufacturer and you are trying to figure out how much inventory you have and what in that inventory you should be selling to customers, you have to take data from one system and connect it from other systems to address those questions.

Abbo: Key to effective information retrieval and use is data unification. Using our C3 AI Platform, we unify data from tens or hundreds, or in some cases thousands, of data sources. The challenge with unifying data across systems is that a person, product, or part is referenced with different identifiers in each different system. For example, Nikhil might be represented in one system with his first, middle, and last name, and then in another system, his name is misspelled. The capability to resolve those inconsistencies and provide a 360-degree view of Nikhil is inherently built into the C3 AI’s unique model-driven architecture. The other enabler is information security. We only provide the information as long as the user has the authorization to actually see that information. The C3 AI platform is able to unify petabyte-scale data from enterprise and extraprise sources, analyze it using machine learning models, and provide these predictive insights to users through enterprise AI applications.

How is C3 AI able to help enterprises address these challenges?

Abbo: C3 Generative AI leverages all the work we’ve done as a company over the past 14 years and more than $2 billion in investments in our products and R&D. It complements our entire stack of industry-leading enterprise AI platform and industry and business function-specific applications. The C3 Generative AI Suite allows users to have a conversation with data and machine learning predictions contained in our enterprise AI products through a search bar interface. This makes the data and predictive insights accessible and usable to a wide variety of enterprise users.

How does C3 Generative AI for Enterprise Search build upon and enhance these capabilities?

Abbo: The C3 Generative AI Suite is really a game changer in multiple ways. Now that we’ve unified data across an organization, we can make it accessible to anybody, from the CEO down to the demand planner or the flatline maintainer. The way we’ve done that is by essentially providing a search-like interface on top of that information. So, now, within an enterprise, a user can simply type in a question, and the system will search across all these systems to get information back. Users don’t have to be trained on all applications. They can simply type natural language questions into the search bar and have the answer retrieved for them. So, if the question is where the supply chain is likely to be disrupted, the search will pull up a map showing the specific supplier route that is likely to have disruptions due to weather or strikes. And then, the concept of reinforcement learning is applied so users can continue to ask questions, so they could figure out what particular link in the supply chain is likely to break or what alternative suppliers they could consider, to satisfy the demand. This is revolutionary from the perspective of changing access to information across an organization.

Can you give an overview of C3 Generative AI’s product functionality?

Krishnan: We thought about what makes today’s search engines so intuitive and user-friendly and adopted the standard that is well-known and understood by everyone. When a user types in a question, the system understands the user’s intent, finds the closest match to answer the question, and surfaces that result in summary text, as well as with the right visualization, such as a chart or graph. Below that top search result, users will see an additional list of relevant links, data sets, or documents. Then, on the right-hand side of the interface, there is a chat experience to allow the user to interact with the system—and the system responds back with full context. Overall, it’s a very intuitive look and feel.

How was the search interface of C3 Generative AI designed to be as familiar and user-friendly for stakeholders as possible?

Krishnan: First is security. We built an architecture that allows our customers to deploy in secure internet air gap environments, private cloud environments, and across multiple cloud providers. Next is accuracy. Our customers want a service that accurately answers the question at hand. And if the service doesn’t know the question at hand, it must communicate that it doesn’t know. So our architecture does just that. And when the system provides the right answers, it accurately and granularly sites the specific sources the information comes from. We also ensure full access controls. If our system is deployed, for example, in the Department of Defense, specific documents have very specific clearance levels. They have role-based access controls, attribute-based access controls, and certain sections of documents may have different classification levels. So we needed to really be able to model granular access controls so two different users would get different answers based on what their permissions are within the same enterprise. The CEO will get an answer that might be much broader than somebody on the front line, or in a manufacturing plant, would get. Another big focus for us was the learning mechanism. How are we going to allow users to provide feedback? When we did our early research last year, one of the things we realized is that representing the enterprise’s knowledge is more than just modeling the documents. A lot of knowledge exists in the brains of operators, and a lot of these operators are retiring and starting to leave the workforce. So what we wanted to do was have a way in which these senior operators could not just comment on the answers, but they could also provide net new content as they’re using the product. We wanted to make it very easy for these people to provide feedback to the system to help our next generation of operators actually learn in a much more efficient way.

What are the key features of C3 Generative AI and what makes it unique?

Abbo: What the product does is take data from all the systems scattered across a company, unify it, and then apply AI and machine learning to make it instantly predictive in nature. So a user can ask questions like “How much inventory should I hold to meet the customer order?” or “Which customers are likely to leave me and what actions should I take to mitigate that?” You can learn not just where the supply chain broke down in the past, but where it is likely to break down in the future. So essentially, we’re not only providing the information across systems, but we’re also making it more actionable so that people aren’t just looking at dashboards that report the past—they’re able to look at what’s likely to happen and take actions accordingly.

Can you describe the predictive capabilities of C3 Generative AI?

Abbo: The C3 AI Platform has an open architecture that’s referred to as the “model-driven” architecture. What this means is that the capabilities we enable are done in a way that’s independent of the specific underlying technologies. Why that’s relevant here is that there are literally billions, if not tens of billions, of dollars being invested in generative AI technologies and large language models across the board, and C3 AI can basically leverage one or more of those large language models in any customer deployment. So, we’re not attached to a specific model, and over time, as more models are introduced in the market, we can take advantage of any of them and future-proof our customers’ investments in these capabilities. Krishnan: Another big part is how we can invoke the right machine learning models, manage the different models, and retrain experiments—all of these capabilities are in our core architecture and would take others a lot of time to develop. We really offer a full enterprise-class product and not a black box.

How does C3 AI’s underlying technology make it a natural leader in the generative AI market?

Krishnan: Changing rapidly is our core business. This is what we wake up and go to bed every day thinking about. Our customers greatly inform our R&D investments because we want to invest and innovate where it’s going to make a material difference to them. We are advised by some of the best academic advisors in the world, and we believe we have the right ecosystem of partnerships to pull this off. It’s a really tight ecosystem with a small set of people who do this sort of stuff. We’re incredibly excited by what our products mean for the enterprise.

How will the C3 Generative AI Product Suite help enterprises stay ahead of the curve?

Listen to Ed Abbo on how C3 AI can leverage any large language model that comes to market.

Listen to Nikhil Krishnan on why the objectives of C3 Generative AI for Enterprise Search are unique.

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Listen to Ed Abbo on how C3 AI can leverage any large language model that comes to market.

Listen to Nikhil Krishnan on why the objectives of C3 Generative AI for Enterprise Search are unique.

The Age of Enterprise AI