Building the Contextual Data Layer for Enterprise AI | Arango Meetup

Large language models can generate impressive responses—but without the right context, they can't consistently deliver trusted outcomes for enterprise AI. In this Arango Meetup session, Ravi Sharma explores why context engineering is becoming a foundational capability for enterprise AI and agentic systems. Through practical examples, he explains how context helps AI agents reduce ambiguity, improve reasoning, incorporate governance, and produce more reliable, explainable results. You'll also learn about Arango's vision for a Contextual Data Foundation, bringing together graph, vector, document, key-value, and search capabilities with AI services to provide the business context needed to power trusted AI applications at scale. What You'll Learn 🧠 Why context is essential for enterprise AI 🤖 The difference between context windows and context engineering 🌐 How contextual data helps AI agents reason with business context 📊 The key layers of a contextual data foundation 🔍 Why retrieval, memory, governance, user intent, and temporal awareness are critical for trustworthy AI ⚡ How connected enterprise data enables more reliable AI agents Topics Covered - Context Engineering - Enterprise AI - Contextual Data Foundation - AI Agents - Knowledge Graphs - Retrieval-Augmented Generation (RAG) - GraphRAG - AI Governance - AutoGraph - Auto-RAG CHAPTERS 00:00 Welcome & What ArangoDB Does 02:25 Meet the Speaker: Ravi's Background 04:34 Defining the Problem: What Is Context? 07:00 What Makes Context Effective — Signal, Meaning & the 5 W's 09:57 From Data to Decisions: The Context Framework 11:33 Building AI Agents in the Human Image 14:00 Mapping Human Intent to Enterprise AI 16:33 What AI Actually Sees: Training, Prompts & Tools 17:56 Understanding Ambiguity Without Grounding 18:49 Why Context Matters in the Agentic Era 20:41 Failure Modes of Underpowered Context 21:40 What an AI Context Layer Needs 24:33 The Layers of Context 25:41 RAG & Grounding Enterprise Knowledge 27:05 Static vs. Real-Time Context 29:38 Introducing Arango's Contextual Data Foundation 31:14 Auto-RAG, AutoGraph & AI Deliverables 33:41 Announcing the New Community Edition 36:49 Q&A: Local LLMs & Context Windows 37:50 Q&A: Graph Features & AutoGraph 41:28 Q&A: Choosing Different LLMs for Different Tasks 42:31 Q&A: Evaluating Context Quality 44:07 Q&A: Connecting SAP, Salesforce & Enterprise Data 45:26 Closing Remarks & Upcoming Events Learn More 🌐 Website: https://arango.ai 📖 Documentation: https://docs.arango.ai 💻 GitHub: https://github.com/arangodb 🔗 LinkedIn: https://www.linkedin.com/company/arangodb/ 📅 Explore upcoming webinars and events: https://arango.ai/resources/events Subscribe for more videos on Contextual AI, GraphRAG, Enterprise AI, Knowledge Graphs, AI Architecture, and Context Engineering.