INTX was created from decades of firsthand experience with one persistent problem in insurance: operational fragmentation. INTX CEO Rob Lewis brings more than 35 years of experience across insurance, reinsurance, software and capital markets, and has seen significant modernization of individual functions but far less of the operating model that connects them.
According to Lewis, there can be underwriting in one system, policy administration in another and claims and finance somewhere else. Reinsurance can then sit downstream from all of them, even though it directly shapes risk transfer, recoverables, financial performance and capital.
He said, “Each system may do its job well, but the business still spends a tremendous amount of time moving information between them and reconciling what happened, often through manual intervention.”
When INTX began, therefore, the question wasn’t how to build a better policy system. The question was: if you built the operating system for an insurer today, how should it work?
“That led us to build reinsurance into the architecture from the beginning and to bring ceded reinsurance, assumed reinsurance and core insurance operations together on one platform,” explained Lewis. “The goal has always been bigger than making existing processes faster. It’s about removing the fragmentation that made those processes difficult.”
The INTX technology
Lewis describes INTX as the (Re)Insurance Operating System. The platform, he remarks, brings together three major operating areas.
INTX Core supports underwriting, policy administration, claims, billing, financial operations, workflow and reporting. Meanwhile, INTX ReinsureConnect manages ceded reinsurance across treaty and facultative business. Lastly, INTX Re supports assumed reinsurance, including treaty administration, claims, premium and loss accounting, capacity and financial operations.
Across all of that sits Tenet, which is INTX’s native intelligence layer. “What is important is how those pieces work together. We did not build separate applications and then try to connect them afterward. They operate on a common architecture and data model,” said Lewis.
The INTX platform is cloud-native, API-first and event-driven. This means that when something happens in the business, the relevant reinsurance and financial context can move with that event.
“That is a big part of what we mean by an operating system. We want the technology underneath the business to reflect the way the business works,” he explained. That architecture is already supporting live insurance and reinsurance operations in production. The objective is one operating context, one financial context and a much clearer view of what is happening across the enterprise.
Pain points
What are the pain points INTX aims to solve for its clients? For Lewis, many of the problems INTX clients face come back to fragmentation.
He stated, “They may have good technology in different parts of the organization, but if those systems do not share the same understanding of the policy, claim, treaty, recoverable and financial transaction, people end up becoming the integration layer. That means spreadsheets, manual allocations, duplicate entry, reconciliation and a lot of time spent figuring out which information is correct.”
Reinsurance makes this particularly visible. A claim can change today, but the corresponding recoverable may not be understood until later. A treaty may affect a policy or portfolio economically, but that information can sit in a separate process. Finance is then required to bring everything back together. “We are trying to close that gap so operational and financial reality stay aligned,’ he said.
By bringing reinsurance into the transaction flow, firms can create a tighter connection between what happens operationally and what it means financially. This can improve recoverable management, auditability, accounting and visibility into gross and net positions.
Scalability suffers when fragmented infrastructure forces firms to add people just to manage complexity. Technology should break that link.
He added, “INTX brings together decades of insurance, reinsurance and technology experience. That operator perspective is built into the platform, which is already supporting live insurance and reinsurance operations in production.”
What sets INTX apart
What sets INTX apart? The biggest difference for Lewis is the way INTX approached the problem it set out to fix.
He explained, “A lot of insurance platforms were built around policy administration, claims or another core function, with reinsurance addressed later through separate modules or integrations.”
This leads to a lot of reinsurance systems ending up as separate applications that sit beside the core. “Our experience operating in insurance and reinsurance led us to a different starting point: reinsurance is part of the architecture of the insurance business. It affects the economics of the policy, the claim, the portfolio and the capital position. It should not sit several steps downstream from those transactions,” explained Lewis.
Ceded, assumed and core insurance operations can run within the same INTX architecture, allowing carriers to modernize ceded reinsurance through ReinsureConnect without replacing their core environment.
A reinsurer can deploy INTX Re, but another organization may choose the broader platform. “The difference is that those paths can lead to the same operating foundation rather than another collection of disconnected systems. Tenet adds another dimension to that. Because intelligence sits inside the platform, it can work with the underlying insurance context rather than sitting above a group of disconnected applications.”
Why reinsurance remains fragmented
Why has reinsurance remained so reliant on fragmented systems, and what needs to change?
For Lewis, the imbalance is largely historical. Insurance tech investment has long focused on policy production, claims and distribution.
“Reinsurance is one of the most complex and technical parts of the insurance ecosystem, and historically many core platforms were not designed around it. As a result, reinsurance often developed outside the core, touching underwriting, actuarial, claims, finance and accounting without being fully integrated into the transaction flow,” commented Lewis.
In practice, Lewis details, treaty structures vary, portfolios change, companies acquire other businesses, different teams develop their own processes. “Over time, spreadsheets and manual workflows become the connective tissue,” he said.
He continued, “The industry got very good at reconciling fragmentation instead of eliminating it. AI can help bridge disconnected systems, but if it is only being used as a smarter reconciliation layer, the underlying problem remains.”
Lewis said that at INTX, such a reaction is puzzling. “If AI is only being used as better duct tape for disconnected systems, the industry is missing the larger opportunity.“
“The next step for reinsurance technology is not better reconciliation. It is reducing the need for reconciliation in the first place,” said Lewis.
Making AI useful in insurance
A critical question surrounding AI in insurance is how to make it genuinely useful beyond standalone tools.
For Lewis, the biggest issue is context. “The AI models themselves are becoming incredibly capable,” he said. “But insurance is a business where context matters enormously. A treaty clause does not mean very much if you do not understand the treaty, the exposure and the underlying business. The same is true of a policy exclusion or an underwriting guideline. You need to understand how the information relates to everything around it.”
This is why the INTX CEO believes there is a limit to what you can accomplish by simply putting an AI interface on top of disconnected systems.
He continued, “AI needs trusted data. It needs structure. It needs workflow. It needs permissions and governance. Most importantly, it needs to understand the insurance transaction.”
This drove Tenet’s development, embedding intelligence across the operating environment, from treaties and policy terms to underwriting and enterprise knowledge.
However, the larger opportunity for Lewis is what comes next. Much of the discussion around AI is helping people find information or generate answers. The bigger opportunity is for intelligence to safely participate in workflows and decisions.
He concluded, “That requires much deeper context. AI without context can give you an answer. AI with trusted context, inside the workflow, can help you produce a better outcome.”
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