Agentic RAG vs Traditional RAG: Architecting Real-Time AI Data PipelinesRetrieval-Augmented Generation (RAG) solved the initial problem of LLM hallucinations by grounding models in factual data. But traditional RAG architectures share a fundamental flaw: they rely on static data. If you are building an AI agent for finan...May 11 · 9 min readalterlab.hashnode.dev
RAG Pipelines: Why Markdown Extraction Beats HTML for Token EfficiencyFeeding raw HTML into a Retrieval-Augmented Generation (RAG) pipeline is computationally expensive and highly inefficient. Large Language Models (LLMs) operate on tokens, and HTML DOM structures are notoriously token-heavy. When you pipe raw HTML int...1OMay 10 · 6 min readalterlab.hashnode.dev
How to Give Your AI Agent Access to Yahoo Finance DataFinancial AI agents need live market context. Historical training data isn't enough when users ask questions about current stock performance, breaking news, or recent earnings reports. Giving an AI agent programmatic access to Yahoo Finance data allo...May 9 · 5 min readalterlab.hashnode.dev
How to Give Your AI Agent Access to Crunchbase DataDisclaimer: This guide covers accessing publicly available data. Always review a site's robots.txt and Terms of Service before automated access. Do not attempt to access private, authenticated, or paywalled information. To give an AI agent reliable ...May 9 · 9 min readalterlab.hashnode.dev
How to Give Your AI Agent Access to Bloomberg DataDisclaimer: This guide covers accessing publicly available data. Always review a site's robots.txt and Terms of Service before automated access. AI agents require access to real-time ground truth to generate accurate, timely outputs. For agents opera...May 9 · 6 min readalterlab.hashnode.dev
