Your AI strategy is currently hitting a wall. You’ve invested in the models. You’ve built the interfaces. But your AI agents are still failing. They are slow, they are expensive, and they aren’t trusted. This isn’t a failure of intelligence; it’s a failure of reach. This is where agentic lakehouse comes in.
At SIT, we know the hard truth: Agentic AI is only as good as the data it can access, and the context that determines if its answers are safe to act on. If your data is trapped in silos or buried under fragile ETL pipelines, your AI is essentially flying blind and needs to transition to the agentic Lakehouse and Dremio.
The Three Fundamentals of the Agentic Lakehouse
To build AI that actually works for the enterprise, you have to solve for three things. Not one. All three.
1. Unified Data, Zero ETL The old way of moving data—copying, transforming, and loading—is the enemy of AI. It creates “synchronization debt.” Dremio solves this by federating queries across your Iceberg lakehouses, databases, and warehouses. It gives your agents a single, reliable view of the truth without moving a single byte of data.
2. Context for Trusted Answers An AI agent needs to know what “revenue” means in your specific business. We use Dremio’s integrated AI Semantic Layer and Open Catalog powered by Apache Polaris to provide the metadata and business meaning agents need to return consistent results. This isn’t just about accuracy; it’s about governance. Fine-grained, role-based access ensures every agent sees only what it is allowed to see.
3. An Agentic Interface (The MCP Factor) The future isn’t custom integrations; it’s open standards. Dremio connects your AI systems directly to enterprise data via MCP (Model Context Protocol). This is the “USB-C of AI”. It decouples your models from your data, allowing you to swap LLMs without rebuilding your entire stack.
The SIT Implementation: Engineering the Future with the agentic lakehouse in mind
Deploying an Agentic Lakehouse in a complex Israeli environment—integrated with QAD, legacy databases, and secure Oracle infrastructure—requires more than a manual. It requires a partner who understands the plumbing.
We leverage Dremio’s Apache Arrow-based query engine and Columnar Cloud Cache (C3) to deliver lightning-fast performance at the lowest cost. We don’t just “install” software; we implement autonomous, self-optimizing capabilities like Autonomous Reflections and automatic Iceberg clustering. We ensure your agents get answers fast, even on your largest datasets.
The Goal is Simple: Trusted AI.
Stop spending your budget on pipelines that break. Start building the architecture that transforms static AI into a dynamic problem solver.
