XCures Raises $46M to Transform Medical Records with AI

XCures Raises $46 Million to Transform Medical Records with AI

XCures, a startup specializing in the application of artificial intelligence to improve health data management, has recently completed a Series B funding round, raising $46 million. This information was exclusively revealed by Crunchbase News, highlighting the significance of this fundraising for the company's future.

The funding was primarily led by Innovius Capital, with participation from other notable investors such as iGrow and Spring Mountain Capital. This funding round brings XCures' total financing to over $76 million since its inception in 2018. The company's valuation now stands at $127 million, more than double its valuation during the previous funding round of $25 million in December 2023.

Mika Newton, CEO of XCures, stated in an exclusive interview with Crunchbase News: “The healthcare sector has spent decades generating enormous amounts of patient data without a reliable way to make that information usable. We are changing that.”

The Rise of AI Investments in Healthcare

Venture capital investment in AI-driven health and biotechnology companies has seen an upward trend in recent years. According to Crunchbase data, as of June 22, investors have injected approximately $8.5 billion into funding ranging from seed to growth stages for companies in AI-powered health technology categories. By 2025, funding for the sector at all stages totaled $15.8 billion. This year's total is already nearly equivalent to the $8.6 billion raised in this category for all of 2024.

A Pivot to Solve a Problem

Founded in 2018 as a spin-off from Cancer Commons by Marty Tenenbaum, XCures was initially launched to provide decision-support tools for patients with advanced cancer. In its early days, the company focused on patients with refractory stage 3 or 4 cancer diagnoses, where standard care options had been exhausted.

By working with thousands of patients across the country in a direct-to-consumer framework to build its initial model, the company encountered a systemic bottleneck. “What we learned in the process is that decision-making was difficult,” Newton said. “These are complicated but achievable things. But the even harder thing was getting the patient data and information we needed to give them guidance from the start.”

At that time, patient records arrived at the company in FedEx boxes and via fax. This logistical hurdle prompted XCures to pivot to build the underlying infrastructure necessary to connect directly to national healthcare interoperability networks. Today, XCures connects to these electronic exchanges on behalf of its clients, shifting its primary focus to structuring what Newton describes as the industry’s “dirty data.”

“The data in these medical records is incredibly messy, so it’s duplicable. There are images of things, scans of things. There are errors caused by the fact that everything is entered by humans,” Newton explained. “There’s a lot of narrative information, and we’re transforming it into something that is essentially clinical intelligence or the clinical clarity that an organization needs to make its next decisions.”

Creating a “Clinical Clarity Engine”

Patient information remains scattered across thousands of laboratories, hospitals, imaging centers, and electronic medical records, often arriving in the form of unstructured documents that are difficult to use in clinical workflows. This is where XCures can offer a differentiated experience, according to Newton.

“They [competitors] are really in the transport business... moving data from point A to point B,” he noted. “We see our product as the clinical clarity engine of the executor. We are in the business of taking that transported data and transforming it into something that is actually immediately useful, rather than just moving it from one space to another.”

XCures' clinical clarity engine, he said, addresses this issue by integrating capabilities to generate decision-ready checklists from automated patient stories, supported by evidence-quality data. Newton estimates that the engine is three to five years ahead of anyone else in the market. To date, XCures has processed over 300 million medical records from more than 550,000 healthcare facilities across the country, supporting clinical decisions for millions of patients in the United States, according to the company.

To manage this volume without incurring the extreme processing costs associated with running massive, unstructured files through generic models, XCures employs a variety of AI, combining its own internally developed machine learning models with cutting-edge commercial models from existing providers. The company manages these tools through a proprietary governance framework.

“We really see it as the harness for... the process of applying AI, and how we ensure that the tasks we ask the AI to perform are appropriate and well-governed, and that the rules of engagement are really clearly defined,” Newton said.

Strong Growth and Enterprise Adoption

This technological approach has generated impressive traction. Operating on a usage-based SaaS model with committed ceilings, XCures has grown from approximately $3 million to $10 million in annual recurring revenue by 2025, according to Newton, and is on track to exceed $20 million in 2026.

Although XCures reached cash flow break-even last year, the company has intentionally entered a capital consumption phase to build its team for its commercial pipeline in 2027, he added.

The startup's enterprise customer base consists of 25 clients, including laboratory diagnostic companies such as Exact Sciences, Caris Life Sciences, and Novocure. Large hospital networks use the tool to generate “instantly” patient stories for operating room planning, screen for comorbidities, and estimate surgical times before interventions. The engine is also utilized by telehealth providers lacking robust electronic health record architectures, as well as Medicare Advantage plans seeking to automate population risk stratification, prior authorizations, medical necessity documentation, and administrative calls.

Addressing the Most Costly Administrative Work in Healthcare

Ultimately, Newton believes that reducing the immense administrative burden embedded in the U.S. healthcare system is crucial.

“Companies like XCures really reduce the administrative burden and represent the fastest path to realizing value in healthcare for everyone involved,” Newton stated. “This idea that we can use AI not to do things that doctors should do, but simply to make all of this better, easier, faster, cheaper, and better for everyone involved... there’s just a lot of foundational work you should be doing that is really costly, and that’s probably the most immediate opportunity.”

Stu Posluns, a partner at Innovius, wrote in an email that his firm supported XCures because it was impressed by its ability to “locate, extract, and normalize messy data from thousands of incompatible sources.” By applying real clinical context to highlight exactly what is important, the investor noted that Mika Newton and his team are in the process of “building the foundational AI data layer that will power the entire healthcare industry.”