After spending more than two decades helping large enterprises navigate digital transformation—working at companies including Bank of America, Accenture and EY, and later writing a book on the subject—Michael Schank realized he was continuing to encounter the same problem: Organizations were investing millions in change initiatives without fully understanding how they actually operated.
That realization became the foundation for Cary-based Insight Twin. Through this startup, Schank is developing a platform that builds comprehensive digital models of organizations—or “digital twins”—enabling those businesses to gain deeper understanding of their people, processes, systems and risks.
The idea comes at a pivotal moment. As companies race to deploy AI across their structures and operations Schank believes many are skipping the critical first step of building a complete picture of how their businesses actually function.
“Everyone’s like, ‘Yeah, just use AI.’ You’re like, ‘But how?'” Schank said. “You need to know every process, every system, every activity, every person. You need to know everything in one data set.”
The Insight Twin platform
Insight Twin begins the process by pulling operational data from across the business, including information stored in HR systems, technology repositories, risk databases and performance management platforms.
But Schank said even all this data only tells part of the story. Unlike many enterprise AI platforms that rely exclusively on existing company records, Insight Twin also interviews employees throughout the organization to document the work they perform every day.
“A lot of this process knowledge is locked in people’s heads, so you have to talk to them,” Schank explained.
This second prong of data, the institutional knowledge from people that do the jobs each day, is what elevates Insight Twin above other companies aiming to develop digital twins for business intelligence. By combining those conversations with operational data, the platform captures institutional knowledge that may not exist anywhere else, creating a more complete picture of how a company actually operates.
Once the two layers are combined, the platform links each business process to the systems, roles, performance metrics and risks associated with it.
“Now I’m building kind of a model of everything that the business does,” Schank said.
Schank said the model will be continuously refreshed through automated operational data feeds and regular updates, such as a company creating a Center of Excellence and maintaining the data.
Operationalizing the Digital Twin
Once the repository and foundational model of an organization is built, Insight Twin layers AI on top to help companies generate transformation roadmaps, identify operational inefficiencies, eliminate redundant technologies, automate risk assessments and produce project documentation that would oterwise require months of planning. Because every recommendation is grounded in a model of the entire organization, rather than a single workflow, Schank believes the platform can guide enterprise-wide change more effectively than can task-specific AI tools.
“What I think people are missing is that there’s a way to manage the organization, not just individual processes,” he said.
To demonstrate the platform, Schank built a reference model of a retail lending organization, mapping every process involved in originating and servicing loans alongside the systems, risk controls and compliance requirements that support them. That allowed Insight Twin to identify which lending processes are best suited for automation, generate risk assessments, and evaluate the organizational impact of replacing a loan origination platform.
Targets and progress
Schank is targeting medium-sized U.S. companies, wherein he believes organizations can adopt new technology more quickly than large enterprises navigating lengthy procurement processes. His target customers include chief operating officers, chief risk officers and transformation leaders responsible for major organizational change.
QUICK BITS
Startup: Insight Twin
Founder: Michael Schank
Founded: 2026
Team size: 5
Location: Cary
Website: insighttwin.com
Funding: Bootstrapped
Initially, Insight Twin will operate as a hybrid of consulting and software. Because much of an organization’s process knowledge exists only in employees’ heads, building a digital twin requires interviewing employees before AI can begin generating insights. Schank ultimately envisions consulting partners handling that discovery work while Insight Twin focuses on delivering the SaaS platform.
By the end of the year, Schank hopes to have several paying customers and is already in discussions with a midsized regional bank interested in the platform. The startup recently gained local exposure in the Triangle through CED’s spring 2026 GRO Incubator and subsequent, packed Demo Day.
“The ultimate goal is to get the word out that data is key to making AI scale, but it’s not just data.” Schank said. “You need to have a people approach so you can get the right data and validate it.”
