Case study | Energy
Transforming RFQ Configuration and Quoting with AI
Automating complex RFQs to accelerate quoting, reduce configuration errors, and improve accuracy from requirements through final quote.
Overview
A leading electrical power and distribution provider depended on a slow, manual configuration process in which customers completed lengthy RFQ documents by hand. 10Pearls built an AI-powered solution that automated key steps of the quoting and configuration process
with automated workflows
through built-in validation
without added manual effort
Challenge
The configuration process required customers to complete RFQ documents by hand, and those documents were both long and complex. Manual entry left considerable room for error, and mistakes frequently produced configurations that were not valid. Invalid configurations in turn generated inaccurate quotes, a frustrating outcome for both the sales team and the customer, and one that limited how many opportunities could be processed at a time.
Solution
10Pearls developed an automated configuration and quoting solution built around the documents customers already submit. Document extraction reads incoming requirement documents and populates the configuration forms, removing the manual transcription step entirely. A validation engine then checks the resulting values against an existing knowledge base, so invalid combinations are surfaced before a quote is produced rather than discovered afterward.
Building on extraction and validation, guided configuration powered by an LLM connected to the same knowledge base helps users resolve gaps and ambiguous requirements as they work, while inventory matching aligns the completed configuration with available units. Together, these capabilities improved both the speed and the accuracy of quoting, giving the team greater confidence in the configurations behind each quote and the ability to handle higher volumes without a corresponding increase in manual effort.
Top industrial transformer company
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