Generative AI (Gen AI) is transforming manufacturing by enabling advanced data analysis, automation, and faster decision-making. Tools like OpenAI's GPT-3.5 can help further streamline processes, improve data access, and drive innovation. Gen AI solutions—such as chatbots—boost efficiency by providing quick, accurate responses, reducing manual tasks, and increasing productivity. All in all, these factors combined can give manufacturers a competitive edge.
About our client
Our client is a globally recognized manufacturer specializing in industrial test, measurement, and diagnostic equipment. Renowned for their innovative solutions, they serve a broad range of industries, including electronics, industrial automation, and electrical engineering. Their commitment to precision and reliability has established them as a leader in their field.
The issue at hand
The client managed their project lifecycle management data and processes through multiple documents stored on a SharePoint website. While SharePoint also hosted the latest news in the form of .aspx pages, users found it challenging to locate specific documents and extract the necessary information. This lack of efficient data retrieval hindered productivity and slowed down decision-making processes. To address this, the client needed a generalized chatbot that could simplify data access and improve workflow efficiency.
How we stepped in with a Generative AI solution
To address the client’s data management challenges, a chatbot powered by advanced AI technologies was developed. The aim was to create an intuitive system that allowed employees to easily query information from a centralized repository of project-related documents. This AI-driven chatbot not only improved data accessibility but also ensured accurate responses from trusted sources. By integrating Azure AI services with OpenAI’s GPT-3.5 model and Azure Cognitive Search, the solution was built to improve operational efficiency. The chatbot became a critical tool in the client’s project management, enabling faster decision-making and reducing time spent on manual data searches.
The solution was implemented through a multi-step process
that ensured seamless integration of various data sources and technologies:
1. Data
ingestion: Power Automate flows automated the copying of files from
SharePoint and static Excel sheets to Blob storage, triggered by file additions
or modifications. Data included PDFs, Excel files, and .aspx pages to cover the
organization’s document repository.
2. Data
processing: Custom code was developed to decode .aspx pages and extract
relevant text, saved as .txt files for inclusion in the data workflow. Doing
this ensured all formats were accessible to the chatbot.
3. Indexing:
Azure Cognitive Search—a service within Azure AI that specializes in indexing
large volumes of data—indexed data from Blob storage. The service processed
various formats such as PDFs, Excel, and .txt files, creating a searchable index
that served as the chatbot’s backbone.
4. AI
integration: With the data indexed and ready for querying, the next step
involved deploying OpenAI’s GPT-3.5 model. The model was integrated with Azure
Cognitive Search to generate precise, context-based responses using the indexed
data. When a user submitted a query, GPT-3.5 analyzed the ranked results
returned by Azure Cognitive Search and crafted a well-informed answer based on
the indexed data.
5. User
interaction: The chatbot interface, hosted on an Azure WebApp, allowed for
real-time interactions. Cosmos DB stored historical conversations for future
reference and analysis.
6. Additional
features: To further optimize the solution, backend processes were
implemented for data management and cost efficiency. These included converting
old files from Hot to Cold storage and processed data from Cosmos DB into gold
tables for reporting and analysis.
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| Figure 1: Components of the AI-driven chatbot solution |
How the solution yielded business value
Implementation of the AI-driven chatbot solution yielded improvements across the organization’s operations. Through this solution, the organization was able to dramatically improve the accessibility and usability of their project lifecycle management data. The chatbot not only empowered employees to quickly find the information they needed but also facilitated more informed decision-making.
The post-deployment measures demonstrated the effectiveness of the solution:
· Improved
data retrieval time: The time required to locate and retrieve specific
documents or information was reduced drastically, allowing employees to focus
more on high-value tasks.
· Increased
employee productivity: With quick access to accurate information, overall
employee productivity increased. This was measured by the reduction in the
time spent on non-productive activities like manual data searches.
· Reduction
in operational costs: By automating data retrieval and integrating backend
processes like Hot to Cold storage conversion, the organization achieved a large
reduction in operational costs related to data management.
· Increased data accessibility: The centralization and indexing of diverse data formats made 100% of the project lifecycle management data accessible through a single interface. This meant that no critical information was overlooked.
These results underscore the success of the chatbot solution in transforming the organization’s approach to data management. By using advanced AI technologies, the client not only optimized their internal processes but also positioned itself for greater efficiency and competitiveness in the market.
For any further inquiries, contact Sales@MAQSoftware.com to see how chatbots powered by Gen AI can transform your business, improve productivity, and accelerate your delivery.