Inferoa

Inferoa is a specialized agent harness designed for long-horizon coding tasks, focusing on maximizing token efficiency and optimizing inference. Key features include: * Prefix-cache discipline for stable prompt epochs * Context optimization with compression and graph-shaped repo context * Intelligent routing based on cost, safety, and capability * High-throughput, memory-efficient vLLM serving * Multimodal capabilities with vLLM Omni This platform addresses the common mismatch where generic chat traffic from agents negates efficient use of prefix cache, optimal routing, and serving behavior. Inferoa integrates these crucial elements directly into the agent harness, ensuring that context pressure, cache utilization, and route choices are managed deliberately across every turn of a coding session. It leverages the vLLM ecosystem, including vLLM Semantic Router and CodeGraph, to provide a cohesive and performant environment for complex development work. Inferoa is particularly valuable for engineering teams tackling large codebases, evolving project goals, and requiring extensive tool interactions. It ensures that every model call, context window, and serving capacity is utilized efficiently, minimizing wasted tokens and maximizing productivity. The system supports a structured workflow from initial goal setting and plan formulation to execution and autoresearch, keeping objectives, plan status, and evidence visible throughout the task. Ideal for developers and engineering organizations needing to optimize long-running coding projects and improve the cost-effectiveness and speed of development cycles. It's built for those who require robust source code management and high-performance language model serving for intense development scenarios.