Accelerate Your Next Innovation
Founded in 2012, CSLabs is a mission-driven research and software development company dedicated to tackling the most complex technical challenges facing defense and industry today. We deliver innovative, cross-domain solutions that integrate artificial intelligence, machine learning, computer vision, modeling & simulation, and high-performance computing to enable faster, more informed decision-making. From advancing UMV autonomy for naval operations to pioneering mixed-reality point cloud visualization, our solutions are built to perform in demanding, real-world environments.
With expertise spanning multiple domains, we bring a unique perspective to every project we undertake.
Featured Products
Explore our top tools and internal innovations.
Image Processing Xpert (IPX)
Open-source GUI that unifies Python image-processing libraries into a single intuitive workspace
Our Core Values
These principles guide everything we do at CSLabs.
Innovation
We constantly push the boundaries of what's possible, exploring new ideas and approaches.
Excellence
We hold ourselves to the highest standards in every aspect of our work.
Integrity
We operate with transparency and honesty in all our dealings.
Collaboration
We believe that the best solutions come from working together.
Capabilities at a Glance
From software to research, CSLabs provides flexible and innovative solutions.
Data Science
Transforming Data into Operational Insight
Physical Science
Driving Mission Readiness Through Physics
Computer Science
Powering Complex Missions with Advanced Computing
News & Announcements
Stay updated on our projects, team, and future plans.
Navy SBIR Transition Program (Navy STP)
Funded by the DoN SBIR Program, all small businesses with active Navy-funded Phase II SBIR/STTR awards are eligible to participate in the program during the first or second year of their Phase II development and demonstration work. Navy STP participating small businesses achieve a 68 percent greater likelihood of transitioning their technology than those that do not participate.
Read More →CSLabs Awarded Phase I Navy SBIR for Mixed Reality Point Cloud Manipulation
CSLabs has been awarded a Phase I SBIR to develop a mixed-reality system that processes large ship-scale LiDAR and photogrammetry datasets, enabling remote collaboration, real-time anomaly detection, and clash simulations to accelerate modernization timelines
Read More →SeaPort Next Generation (SeaPort-NxG)
CSLabs has been awarded a position on the U.S. Navy’s SeaPort Next Generation (SeaPort-NxG) multiple-award contract vehicle. CSLabs is now eligible to compete for task orders that span a wide range of mission areas, including systems engineering, software development, data analytics, and AI/ML solutions. This award strengthens CSLabs’ ability to deliver advanced, science-driven technologies in support of the Navy’s modernization goals while expanding opportunities to collaborate with government and industry partners.
Read More →CSLabs Awarded a Direct to Phase II Navy SBIR Next-generation Autonomy for Unmanned Maritime Vehicles (UMVs)
CSLabs is advancing AI-Routes, an AI-enabled navigation framework originally developed under an Army Phase I SBIR, to support Navy UMV swarms. Under SBIR contract N00014-24-C-1332, the technology will undergo simulation-based evaluations followed by real-world maritime trials, with additional testing planned to expand capabilities and position the system for future integration.
Read More →CSLabs Awarded a Phase I Army SBIR for AI-Routes - Machine Learning for Breach Routing
CSLabs developed the prototype AI-Routes capability to establish risk predictions and potential breaching routes by using obstacle attributes, expected minefield patterns related to known obstacles, capabilities of current and future breaching technology, information derived from available sensor data, and other data sources (e.g., GIS).
Read More →CSLabs Awarded a Direct to Phase II Army SBIR for Height of Burst Estimation System (HoBES)
End-to-end automated software system for burst detection and height-of-burst calculation. It supports automatic detection of the burst from a video file, utilizing a change detection approach which makes use of multiple computer vision algorithms to process and detect the burst.
Read More →CSLabs Awarded a Phase III Air Force SBIR to Transition Assured and Trusted Microelectronics Solutions (ATMS)
Tomographic and macro-scale AI/ML change detection techniques developed, enabling physical IC (integrated circuits) and PCB (printed circuit boards) reverse engineering and change detection at varying levels of detail
Read More →CSLabs Awarded Phase I Air Force SBIR for Analysis of PCBs Using X-ray Tomography
To address the mission need, CSLabs developed its **XDLayer** technology, a software framework designed to automate sample scanning and optimize 2D and 3D image analysis algorithms. XDLayer maximizes overall system throughput by reducing the number of viewing angles and exposure times required to analyze a sample, while incorporating real-time scanning feedback and image analysis to ensure high-quality reconstruction. By minimizing exposure times, the framework reduces the risk of radiation damage that could impair the functionality of circuits on a PCB, with the possibility of restoring functionality depending on the circuit’s inherent radiation tolerance properties.
Read More →Asynchronous Active 3D Imaging
Traditional active 3D imaging systems, such as airborne and terrestrial LiDAR scanners, use a transmitter and receiver typically co-located on the same platform or connected through synchronous communications (tethered). Where, linear LiDAR imaging systems are deployed from aerial vehicles traveling at speeds of about 90 knots, an altitude of 3000 feet, collecting 8 points per meter over a swath of 3000 feet on the ground. Advanced imaging solutions such as Harris Corporations’ Geiger-mode LiDAR employ an array of sensors generating up to 204,000,000 pulses per second. Where, the Geiger-mode LiDAR employs a conical path, deployed at an altitude of 29,000 feet from an aerial vehicle traveling at 290 knots generating point densities of up to 100 points per square meter (ppsm). Recent advances in LiDAR, detector, and airborne systems technology opened the door to small, high-performance, and significantly lower-cost alternatives to existing airborne LiDAR imaging systems. CSLabs’ proposed initiative leveraged modeling and simulation (M&S) to evaluate the efficacy of new approaches that had the potential to disrupt the existing LiDAR imaging paradigm. Candidate solutions employed low-cost LiDAR system components capable of functioning asynchronously while being deployed in bi/multi-static configurations to support existing and novel concepts of operations.
Read More →XRadIC (DMEA Phase II SBIR) – Analysis of Integrated Circuits Using Limited X-rays
To aid in producing these digital reconstructions, CSLabs developed the XRadIC framework to non-destructively analyze cutting-edge microelectronics using photon flux-limited X-ray microscope systems. The framework coupled on-the-fly sample scanning with online optimized 2D and 3D image analysis algorithms to maximize overall system throughput by dynamically minimizing the number of viewing angles and exposure times needed to analyze a given integrated circuit, while simultaneously scanning and performing image analysis of the circuit’s progress. XRadIC formed the basis of a scalable, extensible platform for failure analysis and reverse engineering. Based on rigorous physics-based simulation, XRadIC’s algorithm development included image stitching, limited-view computed tomography, and 3D segmentation and classification for integrated circuit wiring structures. A key innovation goal of XRadIC was to combine iterative computed tomography methods inspired by compressive sensing with segmentation methods, using as a prior the expected structures of integrated circuits such as planar wiring and binary density classification. This optimization enabled significant reductions in sample analysis times compared with conventional computed tomography algorithms on flux-limited microscope systems.
Read More →CSLabs Awarded a Phase II DARPA SBIR for Foliage Propagation Model Development to Support New Communication Concepts
CSLabs developed the Foliage Abstraction RF Multiscale Estimation Rendering (FARMER) methodology to overcome the limitations of traditional RF modeling. FARMER applies an innovative multiscale calculation approach that dynamically adjusts computational resources and modeling fidelity based on scenario complexity. It integrates acceleration algorithms, parallel processing, and adaptive selection of propagation models to deliver accurate predictions of signal behavior across a broad frequency range (up to 300 GHz). FARMER supports standalone use or modular integration into existing modeling frameworks and is applicable to military RF systems, radar, SAR, sensor networks, and more. The result is a highly flexible and powerful solution capable of simulating realistic RF behavior in dense, cluttered environments.
Read More →Join Our Team
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