Recognition Science offers primary expertise in the design and development of advanced artificial intelligence systems and automated vision systems. Our software is designed using the latest object-oriented design methodologies, with a strong emphasis on C++ development. Our technical staff has decades of experience in numerous development environments and programming languages, including Python, JavaScript, Ada, Basic, C, C++, Fortran, Java, Pascal, and Perl. We leverage modern software development tools and platforms, including Visual Studio, BASH Shell, and leading cloud computing services like AWS, Google Cloud, and Azure.
Areas of Expertise
Our team has extensive experience in developing new feature extraction, clustering, classification, and information measurement algorithms. Additionally, we specialize in generating detailed proposals and reports, understanding software maintainability issues, and managing the software documentation process. Our technical capabilities extend to:
- Large Language Models (LLMs) and Large Multimodal Models (LMMs)
- Self-hosted, secure, and private LLMs
- Vector databases and semantic memory and search
- Retrieval-Augmented Generation (RAG) architecture
Automated Vision Systems
While our primary focus is on AI systems, we also excel in automated vision systems. Our expertise includes multi-look development, multi-sensor fusion, and stereo extraction and processing for visible, infrared, and radar imaging systems. We ensure that all aspects of vision system design, such as camera resolution, perspectives, lighting, and dynamic range, are optimized for accuracy and efficiency.
Cloud Computing and Integration
Our proficiency with cloud computing platforms like AWS, Google Cloud, and Azure allows us to develop scalable, reliable, and secure AI and vision systems. We integrate cloud services to enhance system capabilities, providing robust solutions for complex problems.