Structured comparisons

• AI Agent vs Chatbot — A chatbot converses and often answers or routes requests. An AI agent can also use approved tools to advance a workflow under guardrails, with escalation when risk or uncertainty is high.
• OCR vs Document Intelligence — OCR turns images into text. Document intelligence classifies documents, extracts structured fields, validates them, and routes results into business systems.
• AI Copilot vs AI Agent — A copilot helps a person think and draft with grounded evidence. An agent can take tool-mediated steps in a workflow, still under guardrails and often with human approval for consequential actions.
• ERP vs CRM — ERP manages core operational transactions (finance, inventory, manufacturing). CRM manages customer relationships (leads, accounts, opportunities, service). AI integration typically extends both without replacing them.
• Traditional Automation vs AI Automation — Traditional automation executes defined rules and workflows. AI automation adds interpretation — documents, language, exceptions — but still needs policy boundaries and human escalation.
• Cloud vs On-Premise — Cloud and on-premise are deployment choices driven by data residency, latency, cost, and operating model. Enterprise AI can run in managed APIs, VPC/private cloud, or on-premise model hosting.
• RAG vs Fine Tuning — RAG grounds answers in retrieved enterprise content at query time. Fine tuning adapts model behavior from training data. Enterprises often need RAG for facts and may use fine tuning for style or specialized recognition.

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