AI Semantic Layer
Provides the business context AI agents and humans need to understand data and deliver trusted answers.
The Business Context Layer for Your Agentic Lakehouse
Dremio's AI Semantic Layer provides the definitions, relationships, and metadata that AI agents and analysts need to discover relevant tables, understand business terms, and generate accurate queries—delivering trusted insights across your entire data ecosystem.
Build virtual datasets effortlessly
Create views, virtual datasets, or even data marts across your entire data ecosystem—no ETL required. Curate and connect data using business terminology, making it accessible to AI agents and users alike.
Enable AI to easily find and understand your data
AI-powered semantic search, supported by rich metadata, makes it easy for both AI agents and humans to find the data they want to analyze. Wikis, labels, and tags—enhanced with generative AI— enrich discoverability. Wikis include detailed column descriptions as well as business context, so agents and users can easily find data and understand its meaning.
Governed and trusted by design
AI initiatives are only as strong as the data behind them. With Dremio, governance is built in from the start. Role, row, and column-level security ensure that users and agents only access the right data, while lineage, wikis, and business definitions establish a single source of truth. This trust layer guarantees that AI outputs are accurate, explainable, and aligned with enterprise standards.
Case studies: See the AI Semantic Layer in Action
Report
Ranked #1 semantic layer vendor by Dresner Advisory Services
Dremio's AI Semantic Layer is recognized as the industry leader, delivering the governed business context, semantic search, and metadata management that AI agents and analytics teams need to drive trusted insights at scale.
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Case Study
Improved Supply Chain with >10x Query Performance and 90% Faster Project Delivery
Dremio's data lakehouse helped Amazon achieve 10x faster query performance and reduce project completion times by 90%.
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Case Study
Global Logistics Leader Maersk Scales Analytics from Zero to 1.6M Daily Queries with Dremio
Maersk transformed its global logistics operations by rebuilding its data infrastructure with Dremio’s open data lakehouse platform. Using Apache Iceberg and a scalable architecture, Maersk achieved 99.97% uptime and grew to 1.6 million daily queries across shipping, trucking, warehousing, and air cargo operations.
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