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Praeses Wins $79M Air Force SBIR Phase III IDIQ Contract

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Praeses Wins $79M Air Force SBIR Phase III IDIQ Contract

Shreveport, La. – September 29, 2026 -- Praeses has secured a Small Business Innovation Research (SBIR) Phase III Indefinite Delivery, Indefinite Quantity contract with Air Force Global Strike Command carrying an initial ceiling value of $79 million over a five-year term.

Single-award vehicle opens federal-wide access to Praeses technology

The contract, issued by the General Services Administration's Federal Acquisition Service Assisted Acquisition Services Innovation Office, is structured as a single-award vehicle. It gives AFGSC and eligible customers across the U.S. government a direct procurement path to Praeses' data fusion, management and AI-powered analytics products and services.

Deal targets Battlespace Awareness, JADC2 and nuclear command systems

The award expands the Government Programs division of Praeses to address Department of War requirements in Battlespace Awareness, Joint All Domain Command and Control, and Nuclear Command, Control and Communications. SBIR Phase III awards are designed to move technologies developed under the SBIR program from research into operational deployment.

Former GSA administrator says contract accelerates agency access to innovation

Emily Murphy, former GSA Administrator and advisor to Praeses, said the contract creates a new path for government customers to access Praeses' data fusion and visualization capabilities, developed through years of competition, to support better-informed decisions.

Company links award to job creation in Louisiana's Fourth Congressional District

Praeses Chairman and CEO Nil Shah said the award allows the company to create more high-paying jobs and support economic growth in Northwest Louisiana. House Speaker Mike Johnson, representing Louisiana's Fourth Congressional District, credited the award to collaboration between private-sector expertise and the federal government.

Praeses' core capabilities combine data integration from disparate sources with predictive analytics and large language models to transform complex data into usable operational views.

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