OmniSolve

Our submission is a robust, general-purpose AI agent designed to excel across a wide array of natural language capability domains. Built securely inside a Docker container, it reads multi-domain challenges—ranging from factual knowledge and text summarization to complex mathematical reasoning and code debugging—and executes them using high-performance open-source models via Fireworks AI. To ensure the agent stays well within the 10-minute evaluation threshold while processing tasks at scale, we optimized the execution pipeline with concurrent multi-threading. The agent is strictly compliant with the hackathon's scoring requirements: it seamlessly adapts to injected environment variables, exclusively routes inference through the judging proxy for fair token counting, and includes cross-platform (linux/amd64) compatibility out of the box. By prioritizing exact adherence to task instructions over generalized output, our agent maximizes accuracy while minimizing unnecessary token generation, achieving an optimal balance between intelligence and efficiency.