In the ever-evolving data integration landscape Cambridge Semantics has emerged as a frontrunner. This is in large part due to the forethought of building a software platform, Anzo, that is perfectly suited to partner with technologies pushing advancements in the consumption of natural language. By integrating underlying data sources, Anzo creates a knowledge graph that forms a natural bridge for language models to take advantage of.
As you’ve probably read, Cambridge Semantics has developed a new prototype - Knowledge Guru which harnesses the potential of generative AI and large language models (LLM) to provide a ChatGPT-like interface where any member of an organization can ask questions about their data.
Using manufacturing as our industry lens in these examples, let’s look at common challenges organizations face:
- Integrating Several Data Sources: Manufacturing companies often struggle with data fragmentation where crucial information is scattered across multiple systems and departments. Anzo solves this challenge by seamlessly integrating various data sources, including enterprise systems, IoT devices, and external databases. Anzo understands the semantics and relationships within the data, enabling automatic integration and harmonization. By providing a unified and comprehensive view of data, Anzo empowers manufacturers to make informed decisions based on accurate and up-to-date information.
- Real-Time Monitoring and Predictive Maintenance: Unplanned equipment failures can significantly impact production and incur substantial costs for manufacturing companies. By collecting data from sensors embedded in machinery and leveraging advanced analytics, Anzo can help identify anomalies and predict potential failures. This empowers manufacturers to take timely corrective actions, schedule maintenance activities efficiently, and optimize equipment performance, ultimately improving operational efficiency.
- Supply Chain Optimization: Managing a complex supply chain is a constant challenge for manufacturing companies. By integrating data from various sources, such as ERP systems, CRM platforms, and market data, Anzo facilitates a holistic view of the supply chain. Using Anzo to create a comprehensive understanding enables manufacturers to identify bottlenecks, forecast demand, optimize inventory levels, and enhance collaboration with suppliers, resulting in cost savings and increased efficiency.
Scenario: Driving Investigation with Knowledge Guru
Let's dive into an example use case where Knowledge Guru assists a supervisor addressing quality issues. The supervisor has received reports of failures from the quality assurance team. This investigation begins when one of the team members approaches the supervisor with a defective part.
As the video demonstrates, any member of an organization - even a supervisor or executive with no technical training - can leverage Knowledge Guru to swiftly drive the investigation process. Knowledge Guru combines the power of Anzo with LLM technology to comprehend a user’s questions, correspond them to their organization’s proprietary data, and create a query that returns the relevant result, table, chart, or visualization.
In more complex cases, it may suggest a series of questions. In the video, the supervisor uses Knowledge Guru to identify a flawed component (C-1880), as well as suggest properties of that component that could be a potential root cause. Armed with this knowledge, the supervisor can then collaborate with their team, prioritize remediatory actions, and prevent future occurrences of this defect.