Yes, AXYS automatically caches responses to common and repeated questions. This means that when the same or similar queries are asked again, the system delivers instant answers from the cache instead of running a new AI computation—dramatically reducing compute and token costs. This caching feature helps maximize efficiency and keeps your operational expenses low, especially
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Yes, AXYS provides real-time visibility into your OpenAI token usage directly within the platform. You can monitor token consumption for each query, track historical usage patterns, and quickly identify cost drivers as you interact with your data. This transparency helps you manage your AI budget, optimize prompt efficiency, and ensure you always have full control
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Yes, AXYS is purpose-built to minimize LLM and OpenAI costs for your organization. By leveraging proprietary Retrieval Augmented Generation (RAG) workflows and intelligent data filtering, AXYS reduces the amount of data sent to AI models—cutting token usage by up to 98.8 percent compared to industry averages. AXYS also provides built-in real-time tracking and monitoring tools
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AXYS is built with its own proprietary Retrieval Augmented Generation (RAG) technology, designed from the ground up to dramatically reduce token usage and operational costs with OpenAI and other large language models (LLMs). By intelligently filtering and delivering only the most relevant, context-rich data to each AI query, AXYS minimizes token consumption—often resulting in up
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AXYS is engineered to dramatically reduce the cost and complexity of AI and LLM usage in your organization. By leveraging advanced retrieval augmented generation (RAG) workflows and intelligent data orchestration, AXYS delivers only the most relevant and concise information to AI models. This targeted approach achieves up to 98.8 percent reduction in token usage, significantly
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