Automation Anywhere Licenses
Past New Requirement Updated
- Agency
-
Food and Drug Administration
Department of Health and Human Services
- Solicitation expected
- Estimated value
- $25,000 to $250,000
- Set-aside
- No set-aside
Forecast facts
- Anticipated award
- NAICS code
- 541519 Other Computer Related Services
- Points of contact
-
- Christopher Scott christopher.scott@fda.hhs.gov
Forecast details come from HHS's procurement forecast. Agencies' dates and values are estimates.
About this forecast
The Food and Drug Administration (FDA) is forecasting a contract for Automation Anywhere Licenses focused on implementing advanced analytical methods and tools for risk analytics. The primary objective is to enhance the agency's capability to aggregate, analyze, and mine data from multiple intelligence sources to improve decision-making in areas such as inspections, training, regulatory cooperation, and surveillance. The estimated solicitation release date is July 1, 2026, with an anticipated contract award date of September 1, 2026.
While specific award values are not disclosed, the contract falls under NAICS code 541519 for Other Computer Related Services and aims to develop a comprehensive approach for statistical analysis of correlations and threats. The point of contact for this opportunity is Christopher Scott, who can be reached at christopher.scott@fda.hhs.gov within the Food and Drug Administration. The contract seeks to integrate intelligence-based threat analysis into risk-based allocation of inspection and testing resources, suggesting a complex, data-driven procurement initiative.
Forecast text
Implement licenses to define analytical methods, tools to foster improved utilization of risk analytics to inform strategies, priority-setting, and timely decision-making in the areas of inspections, training, regulatory cooperation and surveillance. Adopt new approaches to better aggregate, analyze multiple sources of information to fully identify risks and emerging trends based on comprehensive assessments of existing information platforms. The developed approach should include data mining of intelligence related sources to enable statistical analysis of correlations and threats. As an extension, integrate intelligence-based threat analysis into the risk-based allocation of inspection and testing resources.
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