Artificial Intelligence (AI) is already delivering on making aspects of health care more efficient. Over time it will likely be essential to supporting clinical and other applications that result in more insightful and effective care and operations. AI has multiple use cases throughout health plan, pharmacy benefit manager (PBM), and health system enterprises today, and with more interoperable and secure data, it is likely to be a critical engine behind analytics, insights, and the decision-making process. Enterprises that lean into adoption are likely to gain immediate returns through cost reduction and gain competitive advantage over the longer term as they use AI to transform their products and services to better engage with consumers.

Exponential AI is a Healthcare AI Platform company that helps Health enterprises build smarter processes to thrive in an era of increasing demand, dynamism, and complexity. Their Decision Intelligence Platform, Enso, reusable Decision Agent Ecosystem, and broad portfolio of AI solutions seamlessly integrate Decision Intelligence into any process to unlock exponential value.

Nikhil Mendhi, COO, will uncover Exponential AI’s journey in the following conversation

How do you help your  clients take control of their AI journey?

We usually adopt a land and expand strategy for our healthcare clients. We start our customers off with solutions that feature prebuilt, pre-trained decision agents, which enable them to realize immediate value. This is possible because the agents that come with our platform, ENSO are trained on healthcare specific functional domain knowledge. Once we demonstrate value, we enable clients to expand and advance AI using ENSO. We train their teams to leverage our low code, no code user interface to build end-to-end solutions on their own using agents. This gives them confidence and control with their AI journey.

Tell us about decision intelligence and the opportunities it holds for healthcare? 

Decision intelligence (DI) is the application of Artificial Intelligence to make business decisions at scale. It gives enterprise’s ability to make and evaluate decisions made within processes, by co-relating decisions to outcomes. For Healthcare, transforming the manual processing layer to support the explosion of processes and transactions for digital organizations has been tough. Decision intelligence uses AI to augment and scale healthcare’s manual processing layer digitally to meet the industry’s current and future needs.

How does Enso help companies gain more scalability?

As we talked about earlier, today there is a need for healthcare companies to operate smarter autonomous processes that constantly respond and adapt to changing business needs while continuously improving on efficiency and cost metrics.

We enable this transformation using our platform Enso, which greatly simplifies the building, training, orchestration, and management of healthcare decision agents. These agents are easily assembled into Decision Intelligence solutions that deliver autonomous processes. 

Unlike human-intensive processes, agent-driven processes can easily scale to current and future needs and enable true digital scale for modern healthcare organizations.

What are the key healthcare processes you have transformed for your clients?

We have seen fantastic results in Claims Processing, Payment Integrity, Contract Management, Utilization Management, Adverse Event Reporting Automation, Clinical Trials etc. 

How does your solution solve payment problems? 

We have a Payment Integrity (PI) suite of solutions that focus on improving payment accuracy and reducing waste and fraud in the healthcare environment. Our Decision Agent-driven PI solutions enable payers to shift left, i.e., move claim decisions and checks that currently happen postpay to prepay. Such a shift helps payers minimize revenue leakage and avoid costly pay and chase efforts. 

How do you help companies take real-time decisions? 

Currently, most AI applications are run in batch and used limitedly as analytical tools. Any patterns or insights that are identified are tested by analytics experts before they are codified into rules and incorporated into systems. Our Decision-Agent Solutions enable Real-time AI that essentially frees healthcare processes from the limitations of current rule-based, manual approaches that are costly and cannot scale. Our solutions empower payers to apply AI integrated with rules (operating in that context) to decisions and transactions that happen in real-time, like identification of claims likely to be pended, payment errors, existence of COB etc. They can be deployed adjacent to current claims operation systems to flag in real-time any cases in need of investigation. 

What challenges are you solving for healthcare organizations? 

While today AI is witnessing accelerated adoption within healthcare, using it for decision making remains a challenge. For AI to be used for decision making, it needs to be used in collaboration with rules, optimization and other decision-making techniques and embedded into processes as Decision Intelligence. Building, training, and managing decision pipelines is complex and operationalizing it even harder. This stems from the limited capabilities in orchestrating complex systems, lack of the necessary decision infrastructure and complexities in monitoring and maintaining these systems. Enso, our healthcare AI platform solves these challenges by delivering pre-trained decision agents that enable autonomous processes at scale. 

Tell us about Decision Agents and how they help build solutions faster and better. 

Our pre-trained decision agents underpin our ability to deliver autonomous healthcare processes at scale. Through our decision intelligence platform Enso we offer these prebuilt agents that are easily assembled or orchestrated together with custom-built agents and solution components into Decision Intelligence solutions. ENSO solutions can be trained and customized to the organization’s own data for more relevant and contextual decisions. The platform also enables a solution or its constituents (agents) to be reused in other solutions within the enterprise-which means adoption and scaling are easy.


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