ATLAS
Additive Threat Library & Archive Solutions : Physical Training Models
Description
ATLAS was created to provide law enforcement and security professionals with realistic, physical insight into the rapidly evolving landscape of 3D-printed weapons. Understanding emerging threats requires more than theoretical knowledge – it demands direct, hands-on experience.
ATLAS models are high-quality, inert replicas that allow personnel to safely examine, handle, and study components in a controlled training environment. This tangible exposure plays a critical role in building real-world recognition capabilities and operational confidence. For law enforcement organizations, it is increasingly unavoidable to move beyond abstract awareness and ensure that personnel can physically recognize and interpret these threats. ATLAS enables teams to gain first-hand familiarity with the types of objects they may encounter, helping them better understand both the risks and the mechanisms behind them.
The ATLAS portfolio is structured into three distinct model types, each serving a specific training and operational purpose :
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Cutaway SeriesSectioned models revealing internal geometry and mechanical logic, providing exceptional value for recognition, familiarization, forensic learning, technical demonstrations, and evidence interpretation. |
Blue Series
Life-size, completely inert display models designed for identification, awareness training, and classroom instruction. Safe, durable, and supported by a firearm expert opinion from a CIP-member Proof House, provided on request.
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Red Series
X-ray–accurate screening models engineered with internal inserts that replicate realistic X-ray signatures. Designed for aviation security, border screening, and red-team exercises. Fully inert and independently proof-tested. Expert opinion available on demand.
By combining physical realism with structured training value, ATLAS supports organizations in building a deeper, experience-based understanding of emerging threats. It enables scalable training across teams, enhances recognition capabilities, and ensures that personnel are better prepared to identify and respond to the evolving challenges posed by additive manufacturing.