TextQL has launched a new healthcare vertical that brings AI agents to the intricate data challenges faced by the industry.
TextQL Healthcare is supported by an executive advisory board comprising leaders from organisations that cater to more than 120 million individuals in the US.
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The vertical signifies the company’s move towards reshaping the way providers, payers and health systems extract intelligence from their data.
It develops autonomous AI agents designed for data-intensive tasks within healthcare organisations.
The agents perform data reconciliation, data analytics and data integration workloads by writing and executing Python, SQL and analytical code in healthcare-compliant execution environments.
They traverse several tables across various systems of datastores and records.
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By GlobalDataTextQL’s platform addresses healthcare data management challenges, including disparate fragmented systems and electronic health records in which 90% of data requests remain unfulfilled due to a skilled analyst shortage.
AI agents shorten processes that previously consumed days of manual effort to seconds.
TextQL Healthcare has joined forces with Lumeris to incorporate AI-driven analytics into care management workflows.
The collaboration links TextQL’s platform with Lumeris’ data infrastructure, allowing autonomous AI agents to interrogate complex datasets and provide actionable insights to care teams, without the need for SQL or conventional reporting tools.
It aims to removes technical obstacles that exist between clinical teams and their data, and demonstrates how AI agents can enhance value-based care operations while alleviating administrative burdens as healthcare organisations manage quality requirements and patient populations.
Lumeris engineering senior vice-president Harigovind Singh stated: “TextQL enables analytics to work across our clinical and business teams to merge a multitude of data sources, analyse population health trends, and extract actionable insights in real time. This directly translates to major operational efficiencies and productivity improvements.”
