Parabole
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About
Parabole is a specialized Causal AI platform designed for the enterprise, primarily serving the manufacturing, oil and gas, chemical, and pharmaceutical industries. Its core platform, TRA_I_N, focuses on bridging the gap between Information Technology (IT) and Operational Technology (OT) data. Unlike traditional machine learning that relies on statistical correlations, Parabole utilizes causal theory to understand the underlying mechanisms of industrial processes. This approach allows the system to not only predict outcomes but also explain the logic behind specific interventions, providing a clear path to understanding why certain actions are recommended and how they impact the overall operation. The platform operates as a no-code system, enabling both data scientists and non-developers to rapidly generate ontologies and causal models. This accessibility allows organizations to infuse subject matter expertise directly into the AI, which is particularly useful when high-quality data is scarce. By blending expert knowledge with available data, TRA_I_N acts as a substitute for data gaps that would otherwise hinder traditional data-centric AI models. The system also features pre-built solution templates for various industrial use cases, which helps enterprises scale their AI initiatives more efficiently across different departments and facilities. Parabole is specifically built for roles such as process engineers, supply chain managers, and data stewards within heavy industries. It excels at multi-objective optimization, which is the process of balancing conflicting goals, such as reducing machine downtime while simultaneously maximizing throughput and maintaining sustainability standards. This search for Pareto efficiency ensures that improvements in one area do not inadvertently cause deterioration in another. The platform is also available as a private transactable offer on major cloud marketplaces like Microsoft Azure and Oracle, allowing companies to utilize pre-committed cloud spend for procurement while ensuring compliance with data sovereignty laws. What sets Parabole apart from standard predictive maintenance or analytics tools is its focus on causality over correlation. By identifying the root causes of faults and suggesting remedial actions with automated explanations, it empowers enterprises to move from reactive monitoring to autonomous decision-making. From streamlining procurement planning to optimizing energy consumption and de-carbonization, the platform provides a versatile framework for building Causal AI agents that deliver measurable results across the entire industrial value chain.
Pros & Cons
Blends subject matter expertise with data to overcome data quality gaps.
Provides clear logical paths and explanations for why interventions are proposed.
Supports multi-objective optimization to achieve Pareto efficiency across conflicting goals.
Available as transactable offers on Azure and Oracle marketplaces for easy procurement.
No-code interface enables non-developers to build and validate complex models quickly.
Focused exclusively on heavy industrial sectors rather than general-purpose business use.
Requires integration with complex industrial IT/OT data environments to be effective.
Pricing is not transparent and requires direct contact or marketplace negotiation.
Use Cases
Procurement managers in manufacturing can use causal models to reduce raw material budgets by optimizing purchasing strategies.
Process engineers in Oil & Gas can identify pipeline leaks and receive autonomous explanations for flow anomalies.
Supply chain leads can increase touchless order processing and reduce block remediation time through automated causal agents.
Data stewards can automatically discover business concepts and contextually map them with technical metadata for governance.
Safety officers in chemical plants can deploy systems that provide contextual guidance to improve the safety of new workers.
Platform
Task
Features
• root cause analysis
• multi-objective optimization
• pre-built solution templates
• cloud marketplace integration
• automated ontology generation
• it/ot data integration
• no-code system interface
• causal ai modeling
FAQs
How does Causal AI differ from traditional machine learning?
While traditional ML focuses on statistical correlations and pattern recognition, Causal AI identifies the specific events that cause others. This provides a logical path to understanding why interventions are proposed and how they will impact outcomes.
Can the platform work if I have low-quality data?
Yes, the TRA_I_N platform allows you to blend subject matter expertise with available data. This expert knowledge acts as a substitute for high-quality data, allowing the AI to generate credible results even when data is sparse.
Is a coding background required to use Parabole?
No, Parabole is a no-code system designed for both data scientists and non-developers. Users can quickly generate ontologies and causal models using their own data through an accessible interface.
Where can enterprises purchase the TRA_I_N platform?
The platform is available as a private transactable offer on the Microsoft Azure and Oracle marketplaces. This allows companies to streamline procurement by using their pre-committed cloud spend.
What industries is this tool specifically designed for?
The platform is optimized for advanced manufacturing, oil and gas, and the chemical and pharmaceutical industries. It is built to handle the complex multi-functional challenges typical of these sectors.
Pricing Plans
Enterprise
Unknown Price• No-code causal modeling
• IT and OT data blending
• Multi-objective optimization
• Pre-built solution templates
• Cloud marketplace availability
• Data sovereignty compliance
• Subject matter expert knowledge infusion
• Automated ontology generation
• Private transactable offers
• Root cause analysis
Job Opportunities
AI/ML Engineer
Optimize complex industrial operations and solve multi-functional challenges using Causal AI to bridge the gap between IT and OT data for manufacturing and energy.
Benefits:
Exciting opportunities in software development
Dynamic work environment
Grow your career
Make a significant impact
Tackle real-world challenges
Responsibilities:
Contribute to the commercialization of Causal AI
Tackle real-world challenges
Machine teaching
Modeling
Deployment
Show more details
Technical writer
Optimize complex industrial operations and solve multi-functional challenges using Causal AI to bridge the gap between IT and OT data for manufacturing and energy.
Benefits:
Exciting opportunities in software development
Dynamic work environment
Grow your career
Make a significant impact
Tackle real-world challenges
Responsibilities:
Contribute to the commercialization of Causal AI
Tackle real-world challenges
Machine teaching documentation
Modeling documentation
Deployment documentation
Show more details
Dev Ops
Optimize complex industrial operations and solve multi-functional challenges using Causal AI to bridge the gap between IT and OT data for manufacturing and energy.
Benefits:
Exciting opportunities in software development
Dynamic work environment
Grow your career
Make a significant impact
Tackle real-world challenges
Responsibilities:
Contribute to the commercialization of Causal AI
Tackle real-world challenges
Machine teaching infrastructure
Modeling infrastructure
Deployment infrastructure
Show more details
Ratings & Reviews
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