SourceOne® structures and links data through ontology: a framework that defines entities, attributes, and relationships across the enterprise. Instead of leaving data as isolated tables or files, SourceOne maps it into a knowledge graph where context and meaning are built in. As data is ingested, it is integrated into this framework, embedding both strategic goals and operational workflows directly into the knowledge graph. By leveraging autonomous agents grounded in an ontological data structure, knowledge graphs, and real-time feedback, SourceOne’s AI agents can search, retrieve, and generate intelligence while continuously optimizing outcomes to remain aligned with enterprise objectives.

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Knowledge graphs interlink entities (such as people and concepts) and are a way to visually chart their relationships. Companies like Amazon use knowledge graphs to track buyers’ purchasing habits and suggest other products that might interest them.

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An ontology provides the structure and meaning that allow data, systems, and AI to understand how operational concepts relate to one another. They are a formal representation of concepts or rules within a domain. As the backbone of knowledge graphs, they centralize data and give a shared framework across departments.

This eliminates redundancies and miscommunications. For example, using ontologies, teams from engineering, operations, or finance could access and interpret the same data in ways that are meaningful to their specific needs.

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Ontologies act as the ‘DNA’ of AI systems – defining relationships, hierarchies, and semantic rules that transform raw data into contextualized knowledge. This foundational structure allows AI to reason logically by resolving ambiguities and inferring connections. It also means AI can navigate complexity by mapping multi-layered relationships in domains like supply chains or financial ecosystems and provide well-reasoned answers through precision-driven queries.

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Data teams, with help from the SourceOne® Assistant powered by AI, set up ontological rules for data in a contextual database structure. Most work can be done using natural language.

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When used together, knowledge graphs and ontologies provide a strong highway for AI to traverse without losing context. They offer flexibility within databases and modifications can be made with minimal disruption to any existing systems. With this foundation, AI is more accurate with fewer errors and has more precise semantic understanding.

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A data management system focuses on collecting, storing, and maintaining large volumes of data, both structured and unstructured. It ensures that data is accurate, secure, and accessible. These systems handle everything from text and numbers to images and multimedia, but they don’t interpret or contextualize that data. On the other hand, a knowledge system such as SourceOne® operates more like a brain. It takes stored information, cleans it, and turns it into knowledge, helping you make smarter, faster, and more confident decisions. It captures context, meaning, and expertise so you can see why something is happening, not just what’s happening.

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Oftentimes, companies will assume that there is no off-the-shelf data solution that can meet their needs. That’s another reason why they might choose to create one themselves – a process that can take years. However, there are flexible commercial solutions, such as SourceOne®, that can be configured to meet different needs. Rather than starting from scratch, these solutions serve as a springboard, allowing organizations to harness their data more quickly and innovate only where it’s truly necessary.

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Some companies start small, deploying SourceOne® at a single site or department to solve specific challenges. Others implement it enterprise-wide, connecting existing legacy systems for complete visibility across the operations value chain.

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SourceOne® ingests both structured and unstructured data, connecting it through domain ontology and knowledge graphs, and transforming it into context-rich insight you can use.

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SourceOne® uses a flexible data architecture that can connect to data where it already exists or store it within the system in a centralized repository.

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SourceOne® homogenizes ingested data then uses ontologies and knowledge graphs to structure, connect, and contextualize it. This allows data from different departments, applications, and formats to be understood and analyzed together. By building a living map of your operations, assets, events, decisions, and timelines are linked in a way that makes sense to both humans and machines.

Instead of looking at raw data points, you see the full picture: how equipment failure affected output, how weather patterns correlate with downtime, or how supply delays ripple through your schedule.

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Yes. SourceOne® is designed to connect with a wide range of operational and business systems without replacing them. SourceOne® acts as a bridge to make those applications more useful.

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Yes. SourceOne® EKPS is built so users can work online, offline, and with the same data as other users in real time, automatically tracking and saving all changes.

No. Operational teams can create purpose-built applications using no-code, natural language capabilities.

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The SourceOne® Assistant can answer everything from data interpretation and analysis to predictive and prescriptive operational questions, as well as questions about how to build applications and workflows within the system.

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Yes. You can build workflows, automate processes, and collaborate across teams in real time. Visualizations update instantly, so you’re always working with the latest information. Your original file formats stay intact, and data history is preserved, ensuring traceability.

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Simulation is testing ideas safely. It is the process of building a virtual model of an operation to see how it behaves under different conditions, without changing anything in the real world.

Reinforcement Learning is a type of Artificial Intelligence (AI) technique used for Stochastic Optimization where an agent learns to make decisions by interacting with an environment. It learns by trial and error, receiving rewards or penalties based on its actions and gradually improving its strategy to maximize long-term success.

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Machine User Interface powered by Agentic AI, enables teams to engage with operational data through natural language while sophisticated analytical models run behind the scenes.

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Yes. Instead of navigating complex systems or relying on technical specialists, teams can simply ask questions in natural language and receive clear, contextual answers in a variety of formats, including text, charts, or even 3D visualizations. This capability transforms how organizations access intelligence, simplifying engagement with data and empowering every user to get the information they need, when they need it, to make faster and more confident decisions.

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SourceOne® is designed to secure your data. User- and role-based permissions and access, along with data transfer encryption, all contribute to a modern data governance strategy.

SourceOne® can run on-premise or in the cloud via the SourceOne desktop. Importing data into the system makes it immediately available for use with web-based APIs and other cloud-based technologies. SourceOne doesn’t require cloud infrastructure to function, but with a cloud service provider, the operation will be more efficient. This capability is particularly beneficial for operations in remote areas where access to the public cloud may be slow or unreliable.

We offer a Strategic Start Program: an interactive engagement tailored to your organization’s unique needs. The program provides a hands-on introduction to SourceOne® EKPS, allowing your team to experience the system with your own data while gaining a clear understanding of its capabilities, the business outcomes it enables, and the measurable value it can deliver across your organization. Please contact one of our experts for more information.

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This depends on how your operations are structured, to what scale the system is deployed, and how clean the organization’s data is to begin with. SourceOne can accommodate any situation, but the speed of results depends on the exact situation that it is being rolled out into.

SourceOne® typically drives measurable improvements in productivity, decision quality, operational efficiency, and asset performance. Organizations use it to reduce time spent searching for information, accelerate reporting and analysis, improve forecast accuracy, optimize processes, increase equipment availability, and uncover opportunities to reduce costs and risk. Because SourceOne is highly configurable, the specific outcomes vary by industry, operation, and use case.

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Long-term digital transformation is supported with a connected knowledge foundation. Existing systems are integrated, preserving past investments while making the information more accessible and actionable. As operational needs evolve, SourceOne enables organizations to continuously add new data sources, analytics, applications, workflows, and AI capabilities without rebuilding their digital infrastructure, ensuring the system grows alongside the business.

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The total cost depends on what you want to achieve, how your operations are structured, and the scale at which you choose to deploy. Some companies start small, deploying SourceOne® EKPS at a single site or department to solve specific challenges. Others implement it enterprise-wide, connecting existing legacy systems for complete visibility across the operations value chain. The level of integration and the scope of users all shape the final pricing.

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At Eclipse Data Innovations, you will find a team of forward-thinkers who helped shape the future of data technology. We are a diverse group of individuals who strive to solve some of the most significant large-scale industry challenges.

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Eclipse Data Innovations represents the evolution of more than four decades of experience developing software solutions for complex data in the mining industry. Formerly known as Eclipse Mining Technologies, the company has evolved alongside the industry while expanding its expertise to help other large-scale industries transform fragmented data into trusted knowledge. Today, Eclipse Data Innovations helps organizations make better decisions by preparing their data for AI and the next generation of digital transformation.

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SourceOne® can be applied anywhere organizations need to integrate data, preserve business context, and improve decision-making. While it has deep roots in mining, it is also used across manufacturing, construction, agriculture, oil and gas, energy, logistics, and other asset-intensive industries. Because SourceOne is built around flexible ontologies and knowledge-driven architecture, it can be adapted to the unique processes, terminology, and workflows of virtually any industry.

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