Los Angeles CA (SPX) Jan 19, 2026
Slingshot Aerospace has secured a 27 million dollar contract to modernize how the US Space Force trains for conflict in orbit by embedding its TALOS AI agent into the service's Operational Test and Training Infrastructure program. The 18 month effort will integrate AI native technology into existing training capabilities so that exercises more accurately reflect the rapidly evolving orbital threat landscape and near peer adversary behavior.
The company describes TALOS AI as an autonomous agent that imitates realistic satellite actions for training and simulation. Built on Slingshot's behavior cloning pipeline, the software learns and replicates real world spacecraft tactics within an ever changing orbital environment, allowing operators to rehearse against complex and adaptive scenarios instead of scripted patterns.
Slingshot says the new award advances earlier SpaceWERX and Space Force investments, including a 25 million dollar STRATFI contract from 2022 that helped mature its training and simulation technologies. Under the new contract, TALOS will be used to explore how AI can act as a force multiplier in training by generating machine speed threat behaviors, enabling faster scenario development, larger scale simulations and more realistic mission profiles.
Space Training and Readiness Command has already tested TALOS to assess how AI driven agents can serve as intelligent, unpredictable opponents in exercise environments. During these trials, TALOS produced adaptive behaviors representative of modern orbital maneuver tactics, giving Guardians experience against adversaries that update their strategies in real time during a scenario.
Slingshot is positioning TALOS as a core element in a broader ecosystem of training systems, data sources and AI capabilities that the Space Force can draw on for future exercises. The company is designing the agent and its supporting infrastructure to integrate with complementary platforms from other industry and government partners, with an emphasis on interoperability and mission realism across the training enterprise.
Open application programming interfaces and flexible integration paths are central to the approach. Slingshot says this will allow the Space Force to plug in new sensors, data systems and AI tools as they come online, while still using TALOS as a coordinating layer for threat behaviors and scenario logic.
According to Slingshot chief executive Tim Solms, the contract reflects a shift toward AI native space training where human and machine intelligence work together to give mission leaders an operational edge. He said the system allows Guardians to train against adaptive, AI driven threats that behave like real adversaries rather than pre programmed scenarios, marking what the company calls the dawn of AI native space training.
Slingshot Aerospace, founded in 2017, provides AI powered solutions for satellite tracking, space traffic coordination and space modeling and simulation to government and commercial customers. Its platform fuses data from the Slingshot Global Sensor Network, the Slingshot Seradata satellite and launch history database, satellite owner operators and third party providers to create a common operating picture of space for training, planning and operations.
The company positions this unified view of past, present and predicted space activity as a way to enhance space situational awareness, improve operational efficiency and reduce risk for operators. Slingshot states that its mission is to help keep space safe, sustainable and secure for the growing number of actors relying on orbital infrastructure.
Related Links
Slingshot Aerospace
Military Space News at SpaceWar.com
Slingshot Aerospace has secured a 27 million dollar contract to modernize how the US Space Force trains for conflict in orbit by embedding its TALOS AI agent into the service's Operational Test and Training Infrastructure program. The 18 month effort will integrate AI native technology into existing training capabilities so that exercises more accurately reflect the rapidly evolving orbital thre