How a Global Engineering Manufacturer Reduced Material Review Time, Improved Quality Assurance, and Standardized Compliance Using Artificial Intelligence
For manufacturers operating in highly regulated industries such as oil & gas, energy, power, heavy engineering, and process industries, every incoming material shipment must be accompanied by a Supplier Test Certificate (STC). Before the material can be accepted for production, Quality Control (QC) engineers must verify hundreds of technical parameters against multiple international standards, customer specifications, project-specific Technical Delivery Conditions (TDCs), and manufacturer documentation.
This process was traditionally manual, time-intensive, and highly dependent on experienced engineers. As project volumes increased, the organization faced growing pressure to review certificates faster without compromising quality or compliance.
To overcome these challenges, the organization partnered with VM Micro Analytics to develop an AI-powered Supplier Test Certificate (STC) Reviewer—an intelligent document understanding platform that automates certificate extraction, performs evidence-backed compliance assessment, compares every parameter against applicable standards, and provides AI-assisted recommendations while keeping the QC Engineer firmly in control of the final decision.
Today, the organization reviews material certificates significantly faster, maintains complete traceability, and has established a scalable digital quality assurance process that supports future AI-driven engineering operations.
Every incoming steel plate, pipe, forging, fitting, flange, valve, or fabricated component arrived with a Supplier Test Certificate containing hundreds of technical values. QC engineers spent significant effort validating chemical and mechanical test results against complex codes.
QC engineers spent considerable time locating and comparing chemical/mechanical test results across paper sheets.
Overlapping reference codes from ASME, ASTM, EN, ISO, and API standards, alongside customer-specific Technical Delivery Conditions (TDCs).
Manual comparison of hundreds of minor chemical or mechanical parameters increased the risk of missed deviations.
Quality review consistency was highly dependent on the experience and technical background of individual engineers.
Creating structured documentation and evidence records for regulatory audits required substantial manual effort.
VM Micro Analytics designed and deployed an intelligent AI platform that transforms Supplier Test Certificate review into an evidence-driven digital workflow. Unlike conventional OCR solutions, the platform combines Document AI, Large Language Models, domain-specific engineering reasoning, and retrieval from approved engineering standards to assist QC engineers throughout the review process.
Extracts chemical composition, mechanical properties, dimensions, heat/batch numbers, referenced standards, and test results from digitally generated or scanned certificates.
Identifies the applicable standards and compares reported parameters against ASME, ASTM, EN, ISO, or API codes, explaining governing requirements where codes overlap.
The QC engineer reviews extracted values, AI citations, and rationale, before making the final decision: ACCEPT, REVISE AND RESUBMIT, or REJECT.
Preserves every extracted parameter, AI recommendation, reviewer correction, and final decision, establishing a complete compliance audit trail.
Our structured six-phase implementation methodology ensures seamless transition and rapid user alignment.
Requirement discovery and scoping workshops with QC engineers
Collection of representative Supplier Test Certificates across material grades
Creation of the engineering standards reference corpus (ASME, ASTM, TDCs)
AI model training and prompt engineering customization
Human validation and testing using historical material certificates
Production deployment with controlled rollout across QC functions
AI automated repetitive document analysis, allowing engineers to focus on technical judgment rather than manual comparison.
Every certificate is evaluated using the same approved engineering standards and comparison logic.
QC engineers now spend more time resolving genuine engineering issues instead of locating information across multiple standards.
Evidence-backed recommendations improve confidence during internal audits and customer inspections.
Every engineering decision is supported by documented evidence, citations, and historical review records.
Engineering expertise is embedded into the AI-assisted review process, reducing dependency on individual reviewers.
Planned future roadmap initiatives to scale capabilities and integration.
Syncing reviewed heat numbers and compliance outcomes automatically to the inventory database.
Aggregating compliance variances to score and qualify suppliers based on test certificate quality.
Automatically classifying incoming quality files (STCs, NDT reports, heat charts) into the quality database.
"Reviewing Supplier Test Certificates has always required deep engineering expertise and meticulous attention to detail. The AI-powered STC Reviewer developed by VM Micro Analytics has transformed this process. Instead of spending hours comparing every parameter across multiple standards, our engineers now receive structured, evidence-backed recommendations while retaining complete control over the final decision. The platform has significantly improved productivity, consistency, and audit readiness across our quality operations."— Head of Quality Assurance Engineering & Industrial Manufacturing Company
A leading manufacturer consolidated disconnected ERP, HRMS, and spreadsheets into a unified AI-powered business dashboard, providing real-time KPI monitoring and drill-down analytics for executive decision-making.
An industrial engineering manufacturer deployed an AI-driven operational intelligence platform, integrating production, maintenance, and quality data for real-time performance monitoring and proactive bottleneck identification.
An equipment manufacturer implemented an AI-powered procurement intelligence platform, providing real-time supplier performance scorecards, spend analytics, and early risk detection to improve supply chain resilience.
Explore how VM Micro can help address complex operational, engineering, analytics, or transformation challenges with practical AI solutions.