ContextClue Relaunch: AI Assistant for Engineering and Manufacturing Knowledge Management

At Addepto, we believe that artificial intelligence should not only generate content but also help organizations solve real operational challenges.

Over the last few years, AI adoption has accelerated across many sectors. Yet engineering and manufacturing have remained some of the most complex and under-supported domains – areas where generic AI solutions often fall short.

This gap inspired us to reimagine and relaunch ContextClue as a platform explicitly designed for the needs of industrial environments.

Why Engineering Needed a Different Approach

While generative AI has made remarkable progress in producing summaries, recommendations, and conversational responses, these capabilities alone are not sufficient in production settings.

Engineering teams typically face three core challenges:

1. Fragmented and highly technical data: Information is scattered across CAD drawings, PLM records, ERP systems, maintenance logs, and a long tail of legacy documentation. Unlike typical business documents, engineering content is detailed, specialized, and often context-dependent.
2. Limited search and retrieval capabilities: Conventional document management systems rely on keyword-based search and static taxonomies, making it difficult for engineers to locate relevant information when it’s needed most.
3. Lack of intelligent automation: Even when teams succeed in collecting data, they often lack tools to connect, interpret, and use this information to automate processes such as troubleshooting, commissioning, and predictive maintenance.

Through extensive consultation with manufacturing leaders and engineering professionals, it became clear that generic AI assistants are not equipped to address these issues. ContextClue was re-envisioned to close this gap.

A Platform Reimagined for Industrial Needs

The updated version of ContextClue represents a significant shift from earlier iterations of our knowledge assistant. It is not just a generative AI solution but a modular environment that brings together multiple technologies, including:

• Generative AI: Large language models (LLMs) trained to understand and produce technical content, enabling the creation of summaries, explanations, and recommendations tailored to engineering workflows.
• Knowledge graphs: Semantic representations of data that link documents, system records, and historical information into a unified context, which allows engineers to see how components, processes, and decisions are interrelated.
• Semantic search and retrieval engines: Advanced algorithms capable of interpreting queries in natural language and delivering precise, context-aware results – even when the information is spread across multiple formats and repositories.
• Automation capabilities: Tools that help organizations build digital twins, develop predictive maintenance workflows, and accelerate time-consuming processes such as virtual commissioning.

Supporting Complex Use Cases

By combining generative AI, knowledge graphs, and semantic retrieval, ContextClue helps engineering and manufacturing teams address some of their most complex challenges. The platform can automatically ingest and structure information from diverse sources, including CAD files, technical manuals, compliance records, and maintenance documentation.

With this unified foundation, organizations can develop digital twins that model equipment and processes in detail, improving situational awareness and supporting simulation efforts. Moreover, during virtual commissioning, ContextClue gives teams instant access to critical documentation and configuration histories, significantly reducing the time required to launch new production lines.

Beyond commissioning, the platform also supports predictive maintenance by analyzing operational data to detect early signs of equipment failure, as well as knowledge capture, enabling experienced engineers to record and share best practices in a structured, searchable format.

Early Results and Industry Validation

In a recent proof-of-concept deployment with a global automotive manufacturer, ContextClue demonstrated its ability to drive measurable results. The client needed to carry out virtual commissioning – digitally testing and validating the line before installation.

The process involved:

• CAD drawings, PLM records, and ERP data stored in multiple systems
• Historical logs and vendor manuals
• Tight deadlines for production readiness

ContextClue was implemented to:

• Ingest and organize thousands of documents from CAD, PLM, ERP, and other repositories
• Build a semantic knowledge graph linking related information
• Provide semantic search, so engineers could ask questions in natural language and instantly find relevant answers
• Enable collaborative access to documentation during commissioning sessions

This approach delivered measurable benefits:

• Over 40% reduction in troubleshooting time, accelerating issue resolution
• Improved coordination between engineering and operations teams
• Higher confidence in production readiness and project timelines

Read more: Virtual Commissioning for a Leading German Automotive Manufacturer

Flexible Deployment and Customization Options

One of the huge updates introduced with the relaunch of ContextClue is a new, more flexible purchasing model. Organizations can now choose to adopt the product as a fully integrated, all-in-one solution, combining ingestion, semantic search, and knowledge graph capabilities in a single environment.

Alternatively, companies can select and deploy individual modules independently – for example, starting with semantic search and later adding knowledge graphs or predictive maintenance features as their needs evolve.

This modular approach also supports deep customization, enabling each deployment to reflect specific data sources, workflows, and security requirements unique to the organization. Whether teams need a turnkey platform or a tailored combination of capabilities, ContextClue can be configured to fit diverse engineering and manufacturing environments.

A Focus on the Engineering Community

The relaunch of ContextClue is a direct response to the feedback we received from engineering leaders: they need AI solutions that do more than process text – they need systems that understand engineering data, respect industry standards, and integrate with existing workflows.

ContextClue is purpose-built to:

• Handle complex, specialized terminology and data formats.
• Integrate seamlessly with established ecosystems such as PLM and ERP.
• Support the modular addition of new capabilities as organizations mature in their AI adoption.

Unlike generic AI chatbots or off-the-shelf knowledge bases, ContextClue has been developed specifically for the demands of manufacturing, engineering, and production environments.

Looking Ahead

We believe that the future of engineering knowledge management will be defined by AI systems that combine the best of generative intelligence and structured knowledge representation. The relaunch of ContextClue is an important step in making that vision a reality.

Our tool is designed to serve as a foundation for intelligent, connected workflows that keep pace with the complexity of modern production.

If you’d like to learn more about the new version of ContextClue or discuss a pilot project, please visit: https://context-clue.com