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Workstate Launches AI Document Automation Pro for Government Data Platform to Unlock Data and Create Insights

Workstate

Workstate announced the launch of AI Document Automation Pro for Government Data, a new platform designed to help government agencies, policy leaders, and research institutions unlock critical insights from unstructured data.

Governments and public institutions routinely manage large volumes of information, including eligibility records, program applications, and legacy documents. These must be processed accurately to improve decision-making, compliance, and reporting. The new AI-powered platform enables organizations to enhance data accessibility while maintaining strict security and audit standards.

Also Read: AiThority Interview with Dr. Petar Tsankov, CEO and Co-Founder at LatticeFlow AI

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Key capabilities include:

  • Advanced Data Ingestion and Interpretation: Processes structured, semi-structured, and unstructured documents from sources such as Medicaid, SNAP, TANF, CHIP, and other government data records, as well as scanned legacy files and email correspondence.

  • Flexible, Scalable Architecture: Supports diverse data types and high volumes for programs of all sizes.

  • Automated Compliance Workflows: Classifies, extracts, and organizes content automatically; flags inconsistencies or missing information; streamlines workflows; and enables research, analytics, and auditing.

Proven results back the platform’s accuracy and efficiency. In one case study, Boston College partnered with Workstate to extract data from over 2,300 complex Medicaid PDFs. Using a human-in-the-loop AI pipeline, the project achieved 99% accuracy in just twelve weeks, reducing months of manual work to a rapid, auditable process.

“Institutions face increasingly complex document automation and data harvesting challenges,” said Dennis Allio, CEO of Workstate. “Our AI-powered platform not only accelerates workflows but also ensures data integrity and compliance. We are delivering meaningful impact for agencies and researchers.”

Also Read: Developing Autonomous Security Agents Using Computer Vision and Generative AI

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