Causal AI for the Enterprise
Accelerating advanced manufacturing
Causal AI Platform
Our platform TRAIN, applies causal theory to blend IT and OT data to solve multi-functional optimization
challenges in manufacturing, oil & gas, chemical & pharmaceutical industry
Transforming Industries With Causal AI Agents
From supply chains to asset management, see how our causal AI platform delivers measurable results across critical industrial use cases.
Procurement planning and optimization
TRAIN enabled a leading CPG manufacturer to achieve 10% reduction in annual raw material procurement budget.
Touchless Order processing
TRAIN enabled a leading CPG manufacturer to achieve 10X increase in touchless orders and 70% reduction in block remediation time and lower OTIF penalties.
Energy optimization and de-carbonization
TRAIN enabled a global Oil & Gas major to discover a multi-objective process control strategy for optimizing energy consumption and reducing carbon footprints.
Pipeline leakage detection and remediation
TRAIN enabled a global Oil & Gas major to autonomously formulate hypotheses, identify flow anomalies, and suggest possible leak events with explanations.
Asset performance monitoring and optimization
TRAIN enabled a Chemical manufacturer to autonomously formulate hypotheses, identify root causes for faults and suggest remedial actions.
Production Intelligence-Mass balancing
TRAIN enabled a Chemical manufacturer to recommend corrections for process measurements by analyzing multiple scenarios at once and take remedial measures.
Product design and configuration optimization
TRAIN enabled a fortune 200 Industrial major to build a searchable product master by linking engineering information with customer facing product information.
Employee Health & Safety
TRAIN enabled a Speciality chemical company to build an operational safety system that delivers contextual guidance to improve adaptive capacity of new workers.
Enterprise Data Governance
TRAIN enabled data stewards to automatically discover business concepts, contextually map with technical metadata and curate definitions for Enterprise Data Governance(EDG).
Why Causal AI
Embedding subject matter experts operating knowledge is key to effectively build an AI system
Causation Vs Correlation
Classical data science and machine learning focuses on statistical correlation and pattern recognition. While correlation indicates the relationship between two events, Causation indicates which event causes another leading to superior outcomes. It leaves a complete logical path to “WHY” interventions are proposed and how they positively/negatively impact the outcome.
Expert knowledge + Data
Data-centric AI have a high reliance on good quality data, without which one cannot generate credible results. On the other hand, Causal theory allows blending of subject matter experts knowledge with available data, which acts as a substitute for lack of high-quality data. With data AI no directional understanding can be obtained without sufficient data, which may restrict the avenues that can be explored.
Multi-objective optimization
Most enterprise decisions deals with multiple conflicting objectives which are to be optimized simultaneously to achieve superior outcomes. In most cases, improving one objective often leads to deterioration in another. For instance, procuring lower-cost raw material may increase machine downtime, and raise production costs. Causal theory helps to achieve pareto efficiency where best possible tradeoffs are balanced like reducing machine downtime, maximize machine throughput while retaining product quality and sustainability goals.
Why Parabole
Uniquely designed to automate AI modelling from complex industrial data
Rapid Training, Modeling and Validation
TRAIN’s no-code system allows data scientists and non-developers to quickly generate ontologies and causal models using their own data, for rapid training, modeling, and validation.
Infusing subject matter experts knowledge
TRAIN blends subject matter expertise with available data, acting as a substitute for high-quality data to address data quality gaps.
Scale
Pre-built solution templates makes scaling multiple use cases more efficient.
Experimenting Customers and Partners
Economic Impact through TRAIN Software
John Wick
Designation, Company
Classical data science and machine learning focuses on statistical correlation and pattern recognition. While correlation indicates the relationship between two events, Causation indicates which event causes another leading to superior outcomes. It leaves a complete logical path to “WHY” interventions are proposed.
John Wick
Designation, Company
Classical data science and machine learning focuses on statistical correlation and pattern recognition. While correlation indicates the relationship between two events, Causation indicates which event causes another leading to superior outcomes. It leaves a complete logical path to “WHY” interventions are proposed.
John Wick
Designation, Company
Classical data science and machine learning focuses on statistical correlation and pattern recognition. While correlation indicates the relationship between two events, Causation indicates which event causes another leading to superior outcomes. It leaves a complete logical path to “WHY” interventions are proposed.
TRAIN available on Cloud Marketplace
– TRAIN platform is now available as a private transactable offer on the Microsoft Azure & Oracle marketplace. This streamlines the procurement process and accelerates time-to-value.
– Enterprises can utilize pre-committed cloud spend for Parabole’s transactable offers on the marketplace.
– Fully compliant with data sovereignty laws and regulations.
To schedule a demo
Write to us at info@parabole.ai