Seeking Situational Awareness: Seekr Align LLM Analysis Platform to Reduce LLM Bias and Maximize Decision-Making

The U.S. Army struggles to process vast amounts of data from sensors, intelligence reports, and publicly available information, overwhelming Soldiers and slowing decision-making. Large Language Models (LLMs) offer a solution by automating data synthesis and enhancing operational efficiency. However, trust issues around LLMs, including biases and hallucinations, have hindered adoption. These challenges increase the Army’s risk of falling behind in fast-paced scenarios. SeekrAlign addresses these concerns by introducing an AI-driven LLM platform that reduces bias and improves trust in LLM outputs. It evaluates and refines data with a proprietary Bias Score, analyzing text, audio, and multi-modal content for advanced situational awareness (SA). SeekrAlign’s Principle Alignment (PA) technology, proven over three years in the private sector, uses AI to enhance signal and reduce noise. This approach increases insight generation while minimizing hallucinations and bias. SeekrAlign is proposed as part of the SeekrFlow platform to improve Army LLMs through better data labeling, bias detection, and fine-tuning. Building on Phase I-equivalent work, it offers a solid foundation for Army needs, with proven feasibility and risk mitigation strategies, aligning with SBIR topic requirements.