BeyondAI
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About
BeyondAI is a specialized industrial artificial intelligence platform designed for high-stakes environments where operational errors carry significant financial and safety risks. Unlike traditional AI models that primarily identify patterns or generate text, BeyondAI utilizes a neuro-symbolic approach that combines deep learning with rule-based reasoning. This enables the system to understand context, apply domain-specific constraints, and provide justifiable outputs that human operators can verify. Built on NASA-proven technology used in Mars exploration, the platform is engineered to handle fragmented data and complex regulatory requirements found in heavy industries like energy, utilities, and aerospace. The platform functions through a unified architecture that integrates generative AI with agentic decision systems. A key offering is "AI in a Box," a pre-configured, on-premises solution developed in partnership with Compal. This hardware-software bundle allows organizations to run advanced AI models without cloud dependencies, ensuring data sovereignty and low latency for mission-critical operations. The system's "Operations Advisor" further enhances this by capturing institutional knowledge from experts and embedding it into autonomous workflows, effectively turning reactive maintenance into proactive, self-sufficient management processes. BeyondAI is specifically engineered for professionals in energy, manufacturing, and critical infrastructure sectors who require "decision-grade" intelligence. It is ideal for operations managers, safety engineers, and compliance officers who need AI to operate within strict safety guardrails and provide clear explanations for every autonomous action. By bridging the gap between experimental pilots and production-scale deployment, the tool helps reduce downtime and improve operational efficiency across global industrial sites. What distinguishes BeyondAI from standard Large Language Models (LLMs) or generic machine learning platforms is its focus on explainability and discipline. While pure LLMs may hallucinate or fail to follow rigid physical laws, BeyondAI’s symbolic layer enforces deterministic guardrails based on real-world physics and industry regulations. This hybrid AI approach ensures that every autonomous action is transparent, auditable, and aligned with enterprise-scale ROI, making it a robust solution for moving beyond simple dashboards to true operational autonomy.
Pros & Cons
Utilizes NASA-proven technology for high-stakes industrial reliability.
Provides explainable and justifiable outputs suitable for regulatory compliance.
Offers on-premises deployment options for total data sovereignty.
Combines machine learning with deterministic rule-based reasoning for accuracy.
Supports global enterprise scale across North America, Europe, and Asia-Pacific.
Lacks transparent public pricing models for smaller organizations.
Primarily designed for heavy industrial use cases rather than general business tasks.
Hardware-based on-premise solutions require significant initial infrastructure setup.
Requires strategic consultation rather than offering immediate self-service signup.
Use Cases
Operations managers in the LNG sector can use intelligent document ingestion to improve compliance and safety performance through structured data.
Aerospace engineers can deploy autonomous reasoning systems to navigate complex mission-critical environments where mistakes are extremely costly.
Energy facility supervisors can implement the Operations Advisor to capture institutional knowledge from retiring experts and automate real-time decisions.
Manufacturing compliance officers can utilize explainable AI to ensure all autonomous actions remain within strict regulatory and safety guardrails.
Platform
Features
• knowledge capture workflows
• sovereign generative ai
• domain rule enforcement
• full auditability and explainability
• agentic decision systems
• operations advisor
• ai in a box on-premise hardware
• neuro-symbolic ai engine
FAQs
What is the core technology behind BeyondAI?
It uses Neuro-symbolic AI, which combines the pattern recognition of machine learning with the logic and rule-based reasoning of symbolic AI. This allows the system to follow physical laws and industry regulations while learning from data.
What is "AI in a Box"?
This is an on-premises enterprise AI system delivered in partnership with Compal that includes pre-configured hardware and software. It is designed for organizations that need low latency and complete data sovereignty without cloud dependency.
Can BeyondAI explain its decision-making process?
Yes, the platform is built for full auditability and explainability, providing justifications for its outputs. This is a critical requirement for industries where safety and accountability are paramount.
Which industries benefit most from this platform?
BeyondAI targets high-stakes industrial sectors including Energy, Oil and Gas, Utilities, Manufacturing, Aerospace, and Critical Infrastructure. Its systems are designed for environments where operational risk and uptime are critical factors.
How do we get started with BeyondAI?
The first step is a strategic discussion to assess your operational environment, constraints, and business objectives. From there, the team defines a deployment approach aligned with your infrastructure and enterprise requirements.
Pricing Plans
Enterprise
Unknown Price• Neuro-symbolic AI engine
• On-premises deployment
• Hardware partnership with Compal
• Full auditability and explainability
• Knowledge capture systems
• Secure enterprise infrastructure
• Real-time operational decisioning
• Generative AI integration
• Agentic decision systems
• Strategic strategy session
Job Opportunities
Sales Executive
Deploy enterprise-grade autonomous AI that reasons and explains decisions in high-stakes industrial environments like energy, aerospace, and manufacturing.
Education Requirements:
Bachelor’s degree in business, Engineering, or related field (MBA is an advantage)
Experience Requirements:
Minimum 10 years of experience in sales, account management, or business development within technology, AI, or software solutions
Proven track record in oil and gas sector sales (preferred)
Other Requirements:
Strong knowledge of AI, digital transformation, and enterprise software
Excellent negotiation, communication, and relationship-building skills
Ability to manage multiple stakeholders and complex sales cycles
Willingness to travel as needed
Responsibilities:
Act as the primary point of contact for assigned key accounts, building strong relationships with senior stakeholders
Drive the end-to-end sales cycle including lead generation, proposal development, and contract negotiation
Understand client business needs and challenges in oil & gas digital transformation
Collaborate with internal teams (technical, product, delivery) to ensure tailored solutions meet client requirements
Develop and execute account growth strategies, identifying upsell and cross-sell opportunities
Show more details
Business Analyst - Level 4
Deploy enterprise-grade autonomous AI that reasons and explains decisions in high-stakes industrial environments like energy, aerospace, and manufacturing.
Education Requirements:
BS in Information Systems, Computer Science, Software Engineering, or a related field
Experience Requirements:
8+ years of experience as a BA on technical projects
Experience including software application development, AI solution delivery, and data integration
Preferably experience in Oil & Gas or similar industries
Proven ability to manage and align cross-functional stakeholders toward shared project goals
Other Requirements:
Strong visualization skills using Visio/Lucidchart, Figma/Sketch, and Power BI/Tableau
Excellent communication and active listening skills in Arabic and English
In-depth knowledge of Agile and Waterfall methodologies
Working knowledge of RESTful APIs, database structures, and frontend frameworks
Must be eligible and authorized to work in the Doha (Qatar)
Responsibilities:
Conduct interviews and workshops with business owners and engineers to capture functional and non-functional requirements
Produce user stories, acceptance criteria, process flows, ER diagrams, and UI wireframes
Maintain and prioritize a combined AI/software backlog including data prep and API tasks
Partner with AI engineers, Data Scientists, and developers to validate solutions
Act as liaison between waterfall-oriented stakeholders and agile development teams
Show more details
Business Analyst
Deploy enterprise-grade autonomous AI that reasons and explains decisions in high-stakes industrial environments like energy, aerospace, and manufacturing.
Education Requirements:
BS in Information Systems, Computer Science, Software Engineering, or a related field
Experience Requirements:
3+ years of experience as a BA on technical projects
Experience including software application development, AI solution delivery, and data integration
Preferably experience in Oil & Gas or similar industries
Proven ability to manage and align cross-functional stakeholders toward shared project goals
Other Requirements:
Strong visualization skills using Visio/Lucidchart, Figma/Sketch, and Power BI/Tableau
Fluent in both Arabic and English a must
In-depth knowledge of Agile and Waterfall methodologies
Working knowledge of RESTful APIs, database structures, and frontend frameworks
Must be eligible and authorized to work in the Kingdom of Saudi Arabia (KSA)
Responsibilities:
Conduct interviews and workshops with business owners and engineers to capture functional and non-functional requirements
Produce user stories, acceptance criteria, process flows, ER diagrams, and UI wireframes
Maintain and prioritize a combined AI/software backlog including data prep and API tasks
Partner with AI engineers, Data Scientists, and developers to validate solutions
Act as liaison between waterfall-oriented stakeholders and agile development teams
Show more details
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