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SCWORX ANNOUNCES DEPLOYMENT OF AI-ASSISTED DATA MANAGEMENT MODEL FOR HEALTHCARE SUPPLY CHAIN DATA ATTRIBUTES
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SCWORX ANNOUNCES DEPLOYMENT OF AI-ASSISTED DATA MANAGEMENT MODEL FOR HEALTHCARE SUPPLY CHAIN DATA ATTRIBUTES
Jul 8, 2026 7:11 AM

Middleton, MA, July 08, 2026 (GLOBE NEWSWIRE) -- SCWorx Corp., a provider of healthcare supply chain data management, interoperability and analytics solutions, today announced the deployment of its Artificial Intelligence assisted Data Management Model, a platform designed to automate portions of the SCWorx-controlled data management process and assist with the classification, normalization, enrichment and governance of healthcare supply chain product attributes.

The AI-assisted framework extends SCWorx's existing healthcare data management platform by leveraging its healthcare item database, developed over the past 12 years, together with its proprietary Healthcare Attribute Catalog, advanced UNSPSC methodology and substitute item database.  By combining these differentiated healthcare data assets with commercially available AI models, SCWorx is strengthening its position in healthcare data quality while delivering faster turnaround times for data cleansing and attribute-enrichment projects.

SCWorx is integrating large language model capabilities from industry-leading AI providers into a private environment, with current efforts primarily utilizing Anthropic's family of large language models integrated as one component of the SCWorx-controlled data management platform workflow. In addition to anticipating faster turnaround times for customer data delivery, SCWorx expects these AI tools to assist in accelerating application development, feature creation, bug resolution, data validation and workflow automation, with targeted productivity improvements and cost savings across selected internal development and data management processes. 

Healthcare providers, distributors, group purchasing organizations, manufacturers and ERP platforms rely on accurate product attributes to support purchasing, inventory management, contract compliance, supply disruption mitigation, procedural cost analysis and financial performance. Incomplete or inconsistent data can result in lost revenue, duplicate items, inventory waste, purchasing errors, contract leakage, delayed ERP implementations and reduced visibility into supply chain spending.

SCWorx provides data management services to help healthcare providers and SCWorx partners address these challenges by transforming fragmented and incomplete healthcare product records into standardized, enriched and actionable supply chain information.

The SCWorx AI assisted Data Management Model operates in conjunction with the Company's proprietary healthcare data assets, including millions of normalized healthcare product records, attribute definitions and classification data accumulated through years of healthcare data management engagements. The SCWorx platform is designed to utilize AI models together with the Company's proprietary healthcare product catalog and human quality assurance, including its enhanced UNSPSC-based classification methodology, to improve attribute recognition, classification consistency and data governance across healthcare supply chain data. The Company's proprietary healthcare databases, business rules and classification methodologies provide the domain-specific context used to guide AI-assisted data normalization, classification and enrichment workflows.

“The healthcare industry continues to struggle with fragmented and inconsistent supply chain data,” said Anders Ohlsson, Chief Technology Officer of SCWorx. “Our AI Data Management Model combines advanced AI technologies with SCWorx’s healthcare-specific expertise, proprietary attribute catalog, item substitute intelligence, and enhanced UNSPSC-based classification methodology to improve data quality, accelerate implementation timelines, and provide healthcare organizations with more actionable supply chain intelligence.”

Ohlsson added, "Artificial intelligence is only one component of the solution. SCWorx combines commercially available AI models with SCWorx's proprietary healthcare data and software assets, human QA, classification methodologies and domain expertise. The value comes from that combination, which we believe enables faster turnaround, greater scalability, improved quality and meaningful cost efficiencies for hospitals and health systems. We believe this platform will enable SCWorx to deliver higher-quality results at lower cost and with faster turnaround for our customers and partners."

The underlying AI models are used in conjunction with SCWorx's proprietary software, healthcare databases, business rules and human quality assurance processes, where appropriate, to validate output quality. The AI Data Management Model is currently being deployed across SCWorx's healthcare data management offerings and is being made available to customers on selected engagements, with broader availability expected as implementation progresses.

About SCWorx

SCWorx Corp. is a provider of healthcare data management solutions focused on improving the quality, accuracy, and interoperability of critical healthcare information. SCWorx helps healthcare organizations normalize, cleanse, enrich, and manage supply chain and clinical data to improve operational performance, financial outcomes, and decision-making.

Safe Harbor Statement

This press release contains forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995. Forward-looking statements include, but are not limited to, statements regarding SCWorx Corp.'s expectations, plans, objectives, future operating results, business strategies, market opportunities, product capabilities, customer adoption, anticipated benefits of its technology, artificial intelligence initiatives, partnerships, and future financial performance. These statements are often identified by words such as "anticipates," "believes," "expects," "intends," "plans," "may," "will," "should," "could," "would," "continue," "estimate," "project," "potential," "forecast," or similar expressions.

Forward-looking statements are based on management's current expectations and assumptions and are subject to known and unknown risks, uncertainties, and other factors that could cause actual results to differ materially from those expressed or implied by such statements. These risks and uncertainties include, but are not limited to, the Company may not be able to successfully develop, commercialize, and implement its products and services; rates of customer acceptance of new technologies, including artificial intelligence-assisted solutions, may be lower than anticipated; new technologies may not perform as expected, disruptions stemming from dependence on third-party artificial intelligence providers,  anticipated cost savings, quality improvements or turnaround times may be less than expected; completion of customer implementations may take longer than expected; the Company may not be able to maintain and expand customer relationships as expected; regulatory developments that adversely affect our AI assisted tools; cybersecurity risks related to our technology and proprietary database; and the other risks described in the Company's filings with the U.S. Securities and Exchange Commission.

Readers are cautioned not to place undue reliance on these forward-looking statements, which speak only as of the date of this press release. Except as required by applicable law, SCWorx Corp. undertakes no obligation to update or revise any forward-looking statements to reflect events or circumstances after the date of this release or to reflect the occurrence of unanticipated events.

Investor Relations Contact:

SCWorx Corp.

Investor Relations

Email: [email protected]

Phone: 1-844-472-9679

Image: https://www.globenewswire.com/newsroom/ti?nf=OTc1OTAyOCM3Njk2ODgxIzUwMDA3MjMzNg==

Image: https://ml.globenewswire.com/media/MDYyNmM0ZTAtYjU2Yy00ZWEzLTliZjItNzliMTI4ZDMzOGRhLTUwMDA3MjMzNi0yMDI2LTA3LTA4LWVu/tiny/SCWorx-Corp-.png Image: Primary Logo

Source: SCWorx Corp.

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