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Enterprise Layer Intelligence
Categories/AI Analytics/Promethium
Promethium

Promethium

Founded 2018

Query distributed enterprise databases and generate validated analytics answers using conversational assistants

You can use Promethium to connect your scattered enterprise data sources and run real-time queries without moving your files. It maps your business definitions, catalogs, and rules into a context graph, allowing analysts and assistants to ask questions and receive verified answers. The system works alongside tools like ChatGPT and Claude to supply accurate data context on demand. Analysts can build data products significantly faster, while business teams can explore metrics directly through plain conversational queries without waiting for custom engineering pipelines.

What Promethium does

Run federated SQL queries across disparate cloud warehousesMap semantic business rules into a unified context graphVerify analytical calculations before sharing reports with leadershipFeed structured enterprise data into large language models via APISearch across connected data catalogs using conversational promptsGenerate data models for recurring business analytics questionsLive query engine that queries data across multiple databases without moving filesInsights context graph that maps business rules and metadata to user intentDirect integration with assistants such as ChatGPT, Claude, and CopilotAutomated answer validation before responses reach end usersUniversal context hub consolidating semantic models and data catalogsOn-demand context and data delivery via API for autonomous agentsSingle interface for connecting all organizational data agents

Frequently asked

ClaudeClaudeChatGPTChatGPTMicrosoft CopilotMicrosoft Copilot

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Promethium, enterprise data, context graph, universal query engine, data fabric, agentic analytics, data catalog, semantic layer, SQL queries, data answers, enterprise AI, business intelligence, data federation, text to SQL, automated data analysis