Amazon - AWS; DynamoDB
Past New Requirement Updated
- Agency
-
US Geological Survey
Department of the Interior
- Solicitation expected
- Estimated value
- $250,000 to $499,000
- Set-aside
- Competitive 8(a)
Forecast facts
- Anticipated award
- Through
- Acquisition strategy
- Pre-existing Contract Vehicle - Contract Modification
- NAICS code
- 513210 Software Publishers
- Place of performance
- Augusta, ME
- Forecast number
- 40696
- Points of contact
Forecast details come from the GSA Acquisition Gateway. Agencies' dates and values are estimates.
About this forecast
The U.S. Geological Survey is seeking custom software development services for a unified field data collection web application designed to modernize legacy systems supporting USGS water quantity and quality observing networks. The application will facilitate data collection across approximately 14,000 active time-series monitoring stations as part of a broader software modernization initiative. The solicitation is expected to release on September 1, 2025, with an estimated award date of October 31, 2025.
The estimated award value ranges from $250,000 to $499,000, with a current fiscal year projected obligation of $495,000 and a performance period extending from October 31, 2025, through June 29, 2026. This is a competitive 8(a) set-aside contract classified under NAICS 513210 (Software Publishers) and will be performed in Augusta, ME. Interested parties should contact Sean Jones, Contracting Officer at the U.S. Geological Survey, at smjones@usgs.gov or 303-236-9314 for additional information.
Forecast text
Amazon -AWS; DynamoDB
Custom software development -web app; for a unified field data collection application
Data collection and capture are fundamental to water science and data management. As part of a broader software modernization effort; seeking improvements to legacy field data collection applications by the development of a unified software application. This modernized application would support data collection in the USGS water quantity and quality observing networks. Each year; these include approximately 14000 active time-series monitoring
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