CausalX: A Decision Intelligence Platform

Every critical decision begins with one question, why did this happen? CausalX, developed by Celebal Technologies, answers this with certainty by introducing deterministic root cause intelligence into enterprise decision making. Powered by Microsoft Fabric and Azure AI Foundry, the platform brings together three core components: a unified Data Catalog that consolidates enterprise data, a domain specific Agent Pool that executes structured reasoning, and an Ontology Layer that defines relationships across operations, assets, and financial outcomes.

By combining these components, CausalX establishes true cause-and-effect relationships across enterprise systems. It traces KPI movements, identifies root causes, validates findings with underlying data, and quantifies financial and operational impact before action is taken. Within seconds, enterprises receive complete, explainable outputs including causal pathways, contributing factors, confidence scores, recommended actions with risk context, and a full governance trail. AI supports explanation and action guidance, while root cause determination remains deterministic, ensuring every decision is transparent, auditable, and ready for executive and regulatory scrutiny.

How It Works

CausalX executes a structured causal workflow across enterprise systems:

1. Natural Language Query: Users ask targeted questions (e.g., outage causes, revenue leakage).
2. Data Access via Microsoft Fabric: Relevant operational and financial datasets are accessed from OneLake.
3. Ontology-Based Context Definition: Relationships across assets, processes, and financial metrics are defined.
4. Agent Orchestration via Azure AI Foundry: Domain-specific agents are activated & coordinated to evaluate the problem.
5. Causal Pathway Execution: Agents follow predefined business semantic and logic to determine root cause and contributing factors.
6. Structured Output: Results include root cause, causal chain, supporting evidence, confidence scores, recommended actions, and a governance trail.

Industry Use Cases

Oil & Gas

Upstream

• Production Output vs. Forecast Gap
• Well Equipment Failure Detection

Midstream

• Delivery Delay Root Cause
• Storage Underperformance Analysis

Downstream

• Refinery Yield Shortfall Detection
• Fuel Margin Erosion Root Cause

Power & Utilities

Generation

• Unplanned Maintenance Cost Spike
• Emissions Limit Breach Detection

Transmission

• Grid Instability at Peak Load
• Substation Overload Detection

Distribution & Metering

• Billing Error Root Cause
• Customer Complaint Spike Analysis

Other Industries

Manufacturing

• Production variance root cause
• Supply chain disruption impact

Retail & CPG

• Demand-supply imbalance analysis
• Pricing impact evaluation

Banking & Financial Services

• Transaction anomaly causation
• Credit risk driver analysis

Get Started

Request a Demo to experience root cause intelligence in action.