Prometheux

# **Data that thinks. On Snowflake.**

Prometheux is the context and data processing engine for humans and AI. Process data anywhere it lives, define ontologies once and unlock knowledge that spans databases, warehouses, and platforms.

Deploy Prometheux on Snowflake in one click and run workloads natively on your existing compute, entirely within your Snowflake environment. Maintain authentication, access controls, and boundaries.

Connects to Anything  |  Runs Anywhere  |  Ridiculously Faster

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# Key Capabilities

🔗 **Cross-platform**

Unify and connect data across databases, warehouses, and platforms, with or without migrations. Query PostgreSQL, Neo4j, CSVs, and more, directly in Snowflake, all governed by Snowflake Horizon. One click, one layer, full visibility. No data migration required - data can stay in original sources.

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🕸️ **Native graph analytics**

Create a virtual knowledge graph and run graph analytics natively in Snowflake. Unlock traversals, centrality, shortest-path reasoning, and more, directly on your Snowflake Data Cloud. No GraphDBs, no migrations required.

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⚡️**Faster performance**

Replace 100+ lines of SQL or Python with just a few lines of human-readable logic. Faster than traditional query engines for recursive and graph-style reasoning. Less code. More intelligence.

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**🔄 Seamless migrations**

Move to Snowflake at your own pace - analyze, test, and transform data before, during, or after migration. No complex pipelines, no re-architecture, no downtime. Fast to start, frictionless to scale.

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🧠 **Semantic consistency**

Define business concepts once (like “employee,” “risk score,” “gene”) and reuse them across your entire Snowflake environment. Create a unified semantic layer both humans and AI can understand. One truth, everywhere.

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✨ **Explainable AI**

Feed deterministic knowledge into LLMs for grounded, auditable intelligence. Enhance Snowflake Cortex and other AI tools with structured, explainable context. Trusted answers, every time.

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# 🔍 Industries

**💸 Finance & Financial Services:** Deliver explainable company ownership analytics, fraud detection, and risk scoring while transforming legacy Excel workflows into audit-ready intelligence.

**🧬 Pharma & Life Sciences:** Accelerate drug discovery and patient journey analysis with HCP network mapping and value-level lineage that meets regulatory compliance.

**⚙️ Manufacturing & Operations:** unified risk analysis and traceability for banking compliance reports.

**✨ Enterprise AI & GraphRAG:** Ground LLMs and RAG in deterministic logic for explainable AI that regulated industries trust.

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原始信息汇总

Prometheux数据集概述

数据集基本信息

• 提供商: Prometheux
• 定价: $5,000/月 + Snowflake基础设施费用
• 试用: 15天无限试用

数据集功能与特点

核心功能

• 提供高级符号推理和混合Graph-RAG（检索增强生成）功能
• 无需数据迁移即可集成多样化数据源（PostgreSQL、MongoDB、Neo4j、CSV等）
• 创建虚拟知识图谱进行推理和查询
• 结合Vadalog逻辑规则和基于LLM的问答功能

主要优势

• 提供可解释且确定的洞察
• 支持复杂和碎片化数据集的分析

使用案例

1. 数据谱系与风险传播: 推断故障实体或连接的下游影响
2. 根本原因分析: 跨系统、资产或领域的因果关系推理
3. 供应商/组件智能: 评估供应链中的关键依赖关系和弹性
4. 企业图谱查询: 支持用户对复杂关系模型提出自然语言问题

工作流程

1. 通过Snowflake Marketplace安装应用
2. 设置外部访问集成（如需使用外部数据源）
3. 通过"启动应用"按钮访问UI
4. 上传本地数据集（CSV、Parquet）
5. 连接数据并创建虚拟知识图谱
6. 使用自然语言或基于逻辑的查询与虚拟知识图谱交互

支持的数据源

• 关系型数据库: PostgreSQL、MySQL、Snowflake等
• 文档和图数据库: MongoDB、Neo4j等
• 文件输入: CSV、Parquet、JSON
• 云存储: AWS、Azure、GCP

安全特性

• 符合Native Apps Framework安全要求
• 基于角色的访问控制
• 敏感数据保护
• 事件和日志审核功能

技术示例

数据表示示例

sql Schema of company table in company.csv and in PostgreSQL: |company_id, company_name|

Schema of ownerships graph relationship in Neo4j: |company_from_id, company_to_id, shares|

Schema of risky.parquet file: |company_name,sector|

查询示例

sql q_risk_energy(Company) :- at_risk(Company,Sector), Sector == "Energy". @output("q_risk_energy").

业务需求

• 统一碎片化数据源
• 支持数据质量和身份解析
• 分析供应链依赖关系
• 评估经济影响
• 检测欺诈模式
• 建模风险传播

技术支持

• 销售: [e-mail]
• 支持: [e-mail]

地理覆盖范围

• 全球范围
• 按地区/大陆划分

云区域可用性

AWS

• 亚太地区（孟买）
• 亚太地区（大阪）
• 亚太地区（首尔）
• 亚太地区（新加坡）
• 其他25个区域

搜集汇总

背景与挑战

背景概述

Prometheux是Snowflake平台上的智能数据处理引擎，提供跨平台数据连接、原生图分析和高性能计算功能，支持金融、制药等行业实现可解释的AI分析和数据迁移。