ETL-D FAQs

Question 1

How does ETL-D ensure data reliability and prevent AI hallucinations?

Accepted Answer

ETL-D utilizes a unique 3-layer parsing architecture: Heuristic (100% native deterministic parsers), Semantic (embedding-based alignment), and LLM Shield (strict JSON enforcement). This waterfall approach guarantees precise, deterministic data extraction from complex B2B documents, minimizing hallucination risk.

Question 2

What types of documents and data can ETL-D process?

Accepted Answer

ETL-D specializes in financial and B2B documents, offering native parsers for formats like Norma 43, EDI 850, and broker exports. It also provides document intelligence tools like PDF to spatial Markdown conversion and atomic enrichment for amounts, dates, addresses, and accounting concepts.

Question 3

How can I integrate ETL-D into my AI workflow?

Accepted Answer

ETL-D is built on the Model Context Protocol (MCP), allowing seamless integration with AI agents like Claude Desktop. You can configure it as an MCP server, using its available tools for financial processing, document intelligence, and atomic enrichment to enhance your agent's capabilities.

Question 4

What are the benefits of using ETL-D over direct LLM processing for structured data?

Accepted Answer

Direct LLM processing of raw B2B files often leads to token exhaustion, precision loss due to spatial alignment issues, and non-determinism. ETL-D overcomes these by providing a reliable, cost-efficient, and accurate solution that ensures consistent and high-quality data output for AI agents.

Question 5

What is ETL-D and its main purpose?

Accepted Answer

ETL-D is a deterministic data middleware designed to prevent AI agents from hallucinating over structured data. It achieves this by employing a strict 3-layer parsing architecture via the Model Context Protocol (MCP), ensuring reliable and accurate data processing.

ETL-D

ETL-D

Key Features

Use Cases

Key Features

Use Cases