A global technology and engineering organization sought to streamline quotation generation and improve operational efficiency amid challenges with manual SOW and FSOR document analysis, delays, and error-prone processes. Partnering with TeBS, the organization implemented an AI-powered document processing platform leveraging EKGAI, AWS OpenSearch, SageMaker, and Fargate to automate analysis, generate intelligent cost recommendations, and ensure traceability.
CUSTOMER
Global Technology and engineering organization
REGION
Singapore
INDUSTRY
Engineering Services
FUNCTION
Information technology
Organisation Overview
A leading global technology and engineering group, with a diverse portfolio spanning aerospace, smart city solutions, digital technologies,defence, and public security, focuses on leveraging innovation to address real-world challenges and enhance lives. The organization’s commitment to operational excellence requires accurate, fast, and reliable processes across multiple business functions, including quotation generation.
The Challenges Faced
The organization faced operational inefficiencies in managing criticalproject documentation and quotation workflows:
- Manual Document Analysis: Statements of Work (SOW) and FSORdocuments were analyzed manually, resulting in delays, errors, andinconsistent outputs.
- High Operational Costs: The time-intensive document reviewprocess increased overheads and slowed quotation generation.
- Limited Traceability and Transparency: Task Owners and QCManagers struggled to track document changes, review histories, andapprovals efficiently.
- Inaccurate Quotations: Human errors in cost identification and dataextraction affected the reliability of generated quotations.
Solution Proposed
To address these challenges, the organization consulted with TeBS toimplement an AI-driven document processing system using advancedcloud-based tools:
- Automated Document Analysis: Leveraging Agentic AI (EKGAI), thesolution automatically processes and interprets SOW and FSORdocuments, minimizing manual effort and errors.
- Intelligent Indexing and Search: AWS OpenSearch ensures efficientdocument indexing and retrieval, allowing staff to access requiredinformation quickly.
- AI-Powered Recommendations: SageMaker models provide intelligentsuggestions for cost identification and quotation generation, enhancingaccuracy and decision-making.
- Scalable, Serverless Deployment: Fargate enables seamless, serverlessdeployment, supporting dynamic workloads and ensuring systemscalability.
- Enhanced Traceability and Transparency: The platform tracks alldocument changes and approvals, providing full visibility to Task Ownersand QC Managers.
Benefit
- Faster Quotation Generation: Automated analysis and intelligent recommendations reduce turnaround time, enabling quicker client responses.
- Improved Accuracy: AI-driven cost identification and processing minimize human errors, ensuring reliable quotations.
- Operational Efficiency: Reduced manual effort lowers operational costs and frees staff to focus on higher-value tasks.
- Transparency and Traceability: Full audit trails and approval tracking enhance accountability and confidence in the process.
- Scalable and Flexible System: Cloud-based serverless architecture adapts to workload demands, supporting business growth.
Conclusion
By implementing TeBS’ AI-powered document processing solution, the organization automated SOW and FSOR analysis, improved quotation accuracy, and streamlined workflows. This transformation enhance doperational efficiency, reduced costs, and ensured faster, more reliable responses to client needs—positioning the organization to deliver innovative, data-driven, and future-ready solutions across its technology and engineering portfolio.
