Context Augmented Generation
Traditional Retrieval Augmented Generation (RAG) allows LLMs to leverage information retrieved from your entire database. CAG further augments LLMs with context derived from previous interactions, user data, or domain-specific information, driving more accurate and powerful applications for specific industry-relevant tasks.
Industrial Agent Builder
A low-code tool to create virtual AI assistants focused on solving domain-specific problems with a deep understanding of the industry’s context, terminology, and workflows. Memory 4 Your AI™ walks you through every step of the process:
- Problem Definition and Requirements Analysis
- Data Collection and Preprocessing
- Model Selection and Design
- Training and Optimization
- Continuous Improvement
A low-code tool to create virtual AI assistants focused on solving domain-specific problems with a deep understanding of the industry’s context, terminology, and workflows. Memory 4 Your AI™ walks you through every step of the process:
- Problem Definition and Requirements Analysis
- Data Collection and Preprocessing
- Model Selection and Design
- Training and Optimization
- Continuous Improvement
Engineering Navigator
Understand the potential of you data
Analysis Navigator
Uncover hidden insights
Test Navigator
Automate your test suite
Team Navigator
Build the best team for the job
Risk and Compliance
Monitor and understand compliance and regulations
Engineering Navigator
Navigate connected data across the engineering lifecycle to make faster and more informed decisions. M4AI Agents help trace requirements, link simulations to test results, and answer engineering questions in real time.
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Analysis Navigator
Detect anomalies and discover insights from telemetry data. M4AI Agents correlate runtime patterns with system behavior, supporting faster root cause analysis and design improvements.
Test Navigator
Understand your test coverage and improve test development. M4AI Agents analyze links between requirements, automation results, and test specifications to highlight gaps and opportunities.
Team Navigator
Assemble the right people and tools for complex projects. M4AI Agents analyze project history and skill sets to recommend optimal team configurations.
Risk and Compliance
Stay ahead of regulatory shifts and supplier risks. M4AI Agents track compliance-related data across projects and suppliers to help you act proactively.
Powered by C64-Stack
The C64 Stack is a modular system that turns disconnected engineering and business data into actionable intelligence.
It starts with the Data Context Hub (DCH), which integrates structured, semi-structured, and unstructured data from across your organization into a unified knowledge graph. This graph captures relationships between parts, processes, documents, tests, and more—providing the missing context traditional systems can’t deliver.
It starts with the Data Context Hub (DCH), which integrates structured, semi-structured, and unstructured data from across your organization into a unified knowledge graph. This graph captures relationships between parts, processes, documents, tests, and more—providing the missing context traditional systems can’t deliver.
In the energy sector, optimizing operations and ensuring sustainability is not just about internal data—external factors like climate change, geopolitical shifts, and regulatory requirements play a crucial role in decision-making. Data Context Hub (DCH) enables energy companies to seamlessly integrate operational data with broader contextual insights, helping them navigate these complex challenges.
Solutions
