Data Governance
Who Owns the Context Layer?
The context layer is owned by the data platform team in centralized orgs or domain teams in federated architectures. Learn how to choose the right model.
April 10, 2026Articles & tutorials
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AI Memory Governance
AI Memory Ingestion Pipeline: What Should Enter AI Memory
5 malicious documents caused a 90% false-answer rate. Learn what enters your AI memory ingestion pipeline — and why ingestion governance beats retrieval tuning.
April 8, 2026
AI Memory Systems
AI Memory System vs RAG: The Enterprise Architecture Decision
RAG retrieves from static documents. AI memory persists context across sessions. Both fail when fed ungoverned data. What this means for enterprise AI.
April 8, 2026
AI Agents
What Is an AI Memory System?
AI memory systems give agents cross-session recall. Covers four memory types, the ingestion-eviction lifecycle, 2026 tools, and enterprise memory failures.
April 8, 2026
AI Memory & Data Governance
Context Layer as AI Memory Foundation: Build vs. Connect
Enterprises building AI memory pipelines are duplicating what their context layer already governs. Here's why the build problem is a connection problem.
April 8, 2026
Enterprise AI Glossary
Context Layer Glossary: 10 Terms for Enterprise AI
10 enterprise AI terms defined: Active Ontology, Model Council, Enterprise Memory, Context Graph, and more from Atlan's Enterprise Context Layer.
April 8, 2026
AI Memory Systems
How AI Memory Systems Work: Ingestion, Storage, Retrieval
AI memory systems move through four stages: ingestion, storage, retrieval, and eviction. Ingestion is where source trust is established—or permanently lost.
April 8, 2026
AI Development
How to Add Long-Term Memory to LangChain Agents
How to add long-term memory to LangChain agents using LangGraph checkpointer, BaseStore, LangMem SDK, and ZepCloudMemory, with verified import paths and common pitfalls.
April 8, 2026
AI Memory Systems
Long-Term vs Short-Term AI Memory: The Design Mistake
Short-term and long-term AI memory have different governance requirements. Treating them as one system is the design mistake that breaks enterprise agents.
April 8, 2026
AI Agent Memory
Mem0 Alternatives: 8 AI Memory Layers Worth Considering
Compare the top Mem0 alternatives: Zep, LangMem, Letta, Hindsight, Cognee and more. Benchmarks, pricing, and honest tradeoffs organized by why you are switching.
April 8, 2026
Semantic Layer
What Is a Semantic Layer?
A semantic layer translates raw data into governed business terms. Learn what it is, the main types, and how it powers analytics and AI agents.
April 8, 2026
Context Graph
What Is a Context Graph? Definition, Architecture & Implementation Guide
A context graph links data assets, relationships, and decision history over time. Learn how context graphs power AI agents and audit-ready governance.
April 8, 2026
Context Layer Definition and Enterprise AI Architecture
What Is a Context Layer and Why Do AI Systems Need It?
Learn what a context layer is, core components, key benefits, and where it fits in AI architecture. Practical guide for data and AI teams building intelligent systems.
April 8, 2026
AI Agent Memory
Zep vs Mem0: Which AI Memory Layer Fits Your Stack?
Zep vs Mem0 compared: architecture, benchmarks, pricing, and the enterprise context gap both share. Choose the right AI memory layer for your agent stack.
April 8, 2026
General
Enterprise Context Layer: 54+ Resources for AI Teams | Atlan
54+ resources on what the context layer is, how to implement it, & how to govern it at enterprise scale with Atlan. Reduce AI hallucinations and failed pilots.
April 8, 2026
Enterprise AI Agent Deployment
Why AI Agents Get Stuck in POC Testing Hell (And How to Escape)
88% of AI agent pilots never reach production. The root cause isn't the model — it's missing data context. Learn the 5 failure modes and how to escape.
April 7, 2026
Data Catalog
Your Data Catalog Is Your LLM Knowledge Base
Your data catalog already contains what every LLM knowledge base needs. Learn how to connect it instead of duplicating it, using MCP and active metadata.
April 7, 2026
AI Governance
Enterprise LLM Knowledge Base: Architecture for Data Teams
An enterprise LLM knowledge base requires governed data infrastructure. Learn the 5 requirements CDOs and CIOs must get right before August 2026.
April 7, 2026
Enterprise AI
How to Build an LLM Knowledge Base for Enterprise
Learn how to build an LLM knowledge base for enterprise — from source data governance audit to vector store, retrieval wiring, and freshness monitoring.
April 7, 2026
Data Governance
How to Prepare Data for an LLM Knowledge Base
Learn how to prepare data for an LLM knowledge base using a 7-step governance framework covering classification, deduplication, certification, and freshness.
April 7, 2026
Data Governance
LLM Knowledge Base Data Quality: Governed Data Is the RAG Problem
RAG fails because source data is ungoverned, not because retrieval is broken. Learn the data quality dimensions and failure modes that cause LLM hallucinations.
April 7, 2026
AI and Data Governance
LLM Knowledge Base Staleness: How Active Metadata Fixes It
LLM knowledge base staleness causes confident wrong answers. Learn how active metadata and data catalogs solve freshness where engineering fixes fall short.
April 7, 2026
AI and Data Governance
Best LLM Knowledge Base Tools in 2026
Compare 10 LLM knowledge base tools on retrieval quality, governance, and freshness — including why source data certification is the gap every tool shares.
April 7, 2026
AI and Machine Learning
LLM Knowledge Base vs RAG: What's the Difference?
LLM knowledge base vs RAG: the KB is the data store, RAG is the retrieval layer. Learn how they differ and why KB quality sets the ceiling for every RAG output.
April 7, 2026
