Automating Engineering Document Intelligence for a Gas Technology Leader
Client Overview
PSSPLโs Python experts partnered with a global industrial company with more than 140 years of experience in gas processing and liquefaction technologies. The clientโs sales and bidding teams regularly worked on complex project proposal questionnaires embedded within large technical document sets.
- Teams had to manually review thousands of pages of client specifications and technical PDF documents to find relevant answers.
- This process was time-consuming, repetitive, and prone to error.
- To address this, we designed a simple, reliable solution that enabled engineers to locate answers faster and reduce review time by 80%.
Industry
Industrial Gas Processing
Company size
Enterprise
Location
Germany
Project Duration
12 months
Services Provided
- Enabled bulk PDF uploads.
- Built a system to retrieve the most relevant source-based answers.
- Improved the speed and accuracy of technical questionnaire handling.
- Added live file-processing updates.
- Added Excel export for completed questionnaires.
Technologies Used
Frontend
Next.js
Backend
Python, Flask, REST API, WebSockets
AI & Cloud Services
Azure, OpenAI, GPT-4.0, Azure Event Hubs
The Challenge
The client was facing challenges in handling detailed engineering documents essential for bidding and proposal work. The team had to regularly work with thousands of pages of long manuals, blueprints, technical specifications, and regulatory files. To get specific answers in such extensive document sets wasnโt easy and required more effort.
Senior engineers spent long hours searching for the exact details, which compromised their time for more valuable work. This slowed the process and made it challenging to quickly respond to client requests. Additionally, accuracy was another major issue, because even a minor mistake in this industry can result in costly delays and serious problems.
The company was looking for a solution to quickly identify the right information with the confidence that each answer was based on the right source. They also needed a solution that could make better use of the technical insights stored in their legacy documents in a reliable, simple, and organized manner. The overall challenge was managing the documents while also making the process faster, dependable, and easier for everyday use.
Our Python engineers at PSSPL worked on developing an intelligent document handling solution for a global gas technology leader.
In the original system, the bidding and sales team had to spend significant time searching through the large technical documents to find the right answers. Our customized Python solutions replaced this slow and tiring manual process with a smarter system that could promptly read large documents and provide accurate and relevant answers from the source material. By clearly citing the references, this system helped teams to easily verify each response.
With our approach, the client was able to reduce the document auditing time by 80% and improve the bid response speed by more than 60%.
Manish Langa
AI Practice Head, PSSPL
How PSSPL Helped
The Prakash Software Solutions team of Python developers designed a document intelligence platform to read, organize, and automatically search through large document sets.
The system was designed with the intention to help users easily upload files, track progress, and get answers without any manual intervention. Each time a user asks the question, the system skims through the stored documents to find the most relevant sections and provide answers based on the source information.
We also added an export option to help teams download the completed questionnaire in Excel for quick internal review and sharing.
- Transformed the handling of bid documents for the client by automating the search to give accurate answers in minutes.
- Shortened the bid response cycle, helping teams move faster in handling proposals.
- Preserved valuable company knowledge for modern teams to access and use the data when needed.
Key Features Delivered
Our solution enhanced the document review and questionnaire handling process with the following key features that helped easily manage large technical documents, provide prompt responses, and give reliable answers.
Automated Questionnaire Processing
Without the need for manual search, the system can handle batches of engineering questions automatically. Quickly identifying the most relevant information helps provide accurate responses. This makes the process smooth by avoiding wasted time on repetitive review work.
Live Progress Updates
Users can review the real-time status of document processing, helping teams stay informed without waiting for results. The dashboard reflects what is completed, what is in progress, and what is ready for review as each file moves through the system.
Direct Source Referencing
Every answer is linked to the exact paragraph and page in the original source document. This makes it easy for the engineers to locate the source, confirm the details, and trust the response before using it in reviews for more accountability.
Background Processing for Large Files
The system designed by the PSSPL team of Python engineers handled large document sets without slowing down the user experience. Even if multiple files were uploaded at once, they were processed in the system’s background to keep the interface responsive and easy to use.
Easy Excel Export
Upon completion of the questionnaire, the answers and source details can be exported in the form of an Excel sheet. This one-click export feature makes it easier for teams to review, share, and reuse the output internally.
Knowledge Preservation
The solution made it possible to put years of technical knowledge into use by allowing the client to convert old files into a useful working resource so that teams can make better use of it.
Key Business Outcomes We Delivered
80% Reduction in Document Audit Time
The review process became faster and more efficient, as the clientโs team no longer had to manually spend hours or days searching through large document files for the right information.
Better Use of Engineering Time
Senior engineers had more bandwidth to focus more on actual engineering work, rather than spending time on manual document searching. This improved productivity with valuable expert knowledge in day-to-day operations.
Fast Bid Response Cycle by 60%
As compared to before, proposal teams completed questionnaires and technical checks much more quickly.
Improved Accuracy and Confidence
With every answer having a link to the source document, the team could easily verify the information before using it. This reduced the risk of mistakes, giving managers more confidence in the outcome.
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