Overview
A leading electronics manufacturer partnered with Ironbook.ai to build and deploy two production AI systems: an automated Parts Sales RFQ Engine and an Automated Visual Inspection system, both leveraging AWS serverless architecture for operational excellence. Both solutions are now live in the company's production environment, actively processing sales quotations and manufacturing quality inspections across their operations.
The Challenge
Understanding the business problems that needed to be solved
The company identified two critical operational areas where manual processes were creating bottlenecks and impacting competitiveness:
- 1The parts sales team relied on a manual Request for Quotation (RFQ) process that was slow and error-prone, with personnel spending hours gathering pricing from disparate sources.
- 2Sales staff had to navigate internal price books, customer-specific discount structures, and external vendor catalogs, leading to inconsistent and delayed quotes.
- 3Quality control on the manufacturing floor depended on manual visual inspection, which was labor-intensive and subject to human error.
- 4Defect detection inconsistencies resulted in quality escapes and increased rework costs, impacting customer satisfaction and operational efficiency.
The Solution
How Ironbook.ai delivered a transformative AWS solution
Ironbook.ai developed two integrated AI solutions leveraging AWS serverless architecture:
- Built an RFQ Engine using Amazon Bedrock Agents with AWS Lambda for real-time pricing data retrieval from internal databases and external vendor APIs.
- Implemented natural language processing to interpret customer RFQ emails and automatically extract part numbers, quantities, and specifications.
- Created an Automated Visual Inspection system using Amazon SageMaker for computer vision model training and deployment.
- Deployed AWS Lambda functions for automated quality gating, triggering alerts and routing decisions based on inspection results.
- Established a unified data pipeline using S3 and AWS Glue for both pricing data and inspection image storage and processing.
- Built intuitive dashboards for sales teams and quality managers to monitor system performance and outcomes.
Architecture Diagram
Visual representation of the AWS serverless architecture
Click to enlarge
Technologies Used
The Results
Measurable outcomes and business impact
Since going live in production, the dual AI systems have delivered measurable improvements across the company's sales and manufacturing operations:
70% Faster Quote Turnaround
The production RFQ Engine reduced average quote generation time from 4 hours to under 70 minutes, enabling the sales team to respond to customer inquiries the same day.
30-40% Improved Pricing Accuracy
AI-driven pricing recommendations in production eliminated manual lookup errors and ensured consistent discount application across all customer segments.
95% Defect Detection Rate
The computer vision inspection system operating in production achieved a 95% defect detection rate, significantly reducing quality escapes on the manufacturing floor.
Scalable Production Architecture
The serverless architecture handles variable production workloads with auto-scaling Lambda functions, maintaining consistent performance without manual infrastructure management.
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