RelationalAI: Decision Agent Platform

Key Features

• Semantic Modeling

  Analyzes data inside Snowflake to build a relational knowledge graph that represents business concepts and relationships.

• Multi-type Reasoning

  Supports semantic, natural language, rules-based, graph, predictive, and prescriptive reasoning.

• Snowflake-Native Architecture

  Operates inside Snowflake to avoid data syncs and support data sovereignty.

• LLM Fine-tuning

  Fine-tunes language models on a company's private operational context using a method called superalignment.

• Predictive and Prescriptive Tools

  Includes capabilities designed to help anticipate demand, forecast churn, and support staffing or pricing optimization.

Use Cases

• Supply Chain Management

  Identifying alternative suppliers and calculating the potential revenue impact of shipment delays.

• Inventory Tracking

  Monitoring stock levels and movements across facilities to support allocation and valuation.

• Pricing Optimization

  Setting price floors to help maximize revenue while managing under-delivery risks.

• Demand Forecasting

  Using predictive reasoning to anticipate future sales and potential stockouts.

• Staffing and Scheduling

  Applying prescriptive reasoning to support workforce scheduling.

Integrations

• Snowflake

FAQ

What is a Rel Unit in RelationalAI pricing?

A Rel Unit is a unit of reasoning, similar to a compute hour. It measures the reasoning power consumed by workloads and is billed hourly based on the instance type chosen.

Does RelationalAI work with any database?

The platform is designed as a Snowflake-native system, analyzing data and documents gathered inside Snowflake.

What is the difference between the Standard and Business Critical plans?

The Standard plan provides core functionality like semantic modeling and natural language reasoning. The Business Critical plan adds security features, such as customer-managed encryption keys and private connectivity.