Building an AI Agent That Queries Operational Data (Not Just Chats)
The article discusses the development of an AI agent that can query operational data rather than just engage in chat. It highlights the limitations of generic chatbots in accessing accurate operational data and presents a tool-based architecture as a solution. This architecture allows the AI to use structured query builders to retrieve precise information from databases without generating SQL directly.
- ▪There are two types of AI integrations in operational software: support chatbots and AI agents with structured database access.
- ▪The AI agent built for SampleHQ uses specific query builders to ensure accurate data retrieval without direct database access.
- ▪This tool-based architecture prevents hallucination by constraining the AI model to the results returned by the query builders.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3285408) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Bojan Josifoski Posted on May 20 • Originally published at bojanjosifoski.com Building an AI Agent That Queries Operational Data (Not Just Chats) #react #webdev #opensource There are two kinds of AI integrations in operational software. The first wraps a language model around documentation and lets users ask questions about how the product works. That is a support chatbot. It is useful, but it does not touch operational data.
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