300-500
Request tickets processed automatically every day without manual review
Global Inspection Company Automates Order Processing for 9 Business Lines with Claude
Built an RT and order processing solution on Claude Sonnet through Azure AI Foundry that reads request tickets and notifications across nine lines of business and maps them to BOSS-NGI API payloads for a global testing, inspection, and certification company.
9
Lines of business handled by dedicated Claude skills on one pipeline
3
ERP actions identified and mapped to BOSS-NGI API payloads automatically
Client Overview
Client: SGS India Private Limited
Industry: Testing, Inspection & Certification (TIC)
Company size: Large
Product: Claude Sonnet
Location: Mumbai, India
SGS provides independent inspection, testing, certification, and verification services that help businesses across industries meet standards for quality, safety, and compliance. Their service offering includes laboratory testing for pharmaceutical products and raw materials, inspection and verification services that reduce operational risk for businesses, and certification that confirms products and processes meet regulatory requirements.
Challenges
Every billing change at SGS began as a request ticket or system notification, and the finance team turned each one into an order action in Oracle BOSS ERP. With 300 to 500 tickets arriving daily, reading and re-keying requests crowded out the work of managing billing.
Manual ticket review consumed finance team hours
For every request ticket, a finance team member opened it with any related email or notification, read the unstructured content, and pulled the details Oracle BOSS ERP required. That cycle of reading, extracting, and re-keying repeated hundreds of times a day, with each pass simply moving data between systems.
Nine lines of business ran on nine sets of data rules
SGS's nine lines of business each expect different fields and parameters. Reviewers had to identify the right line of business for each ticket, then structure the data to match its rules. Accuracy depended on who picked up the ticket and how well they knew that business line.
Choosing the right ERP action relied on manual interpretation
Each ticket had to be interpreted to decide which Oracle BOSS ERP action it called for, whether adding a line item, removing a line item, or creating a new order. That decision, along with the information prepared for it, depended on manual interpretation.
Solution
Simform built an AI-powered RT and order processing solution for SGS using Claude Sonnet through Azure AI Foundry. Claude interprets unstructured ticket and email content, identifies the business intent, and structures the information for the applicable line of business before it is mapped to a BOSS-NGI API payload.
Automated extraction and handoff to Claude
Simform used Power Automate Desktop to extract request tickets and notifications and upload the extracted data to Azure Blob Storage. This intake was then connected to Claude through a webhook, which Power Automate Desktop triggers to initiate AI processing of the uploaded data.
Unstructured requests become structured JSON
Simform set up Claude to interpret the unstructured content of each ticket and email and convert it into structured JSON. Alongside the JSON, the solution produces a plain-text Excel representation of the same information.
One pipeline with skills for each line of business
To serve nine lines of business with different data requirements, Simform built a common extraction and orchestration layer followed by LOB-specific Claude skills. Each skill structures the information according to the parameters of its line of business.
Business intent mapped to BOSS-NGI API payloads
Simform configured Claude to identify the business intent of each request, such as adding a line item, removing a line item, or creating a new order. The solution then maps the extracted information to the appropriate BOSS-NGI API payload.
Business Impact
The solution automates the processing of approximately 300 to 500 request tickets per day for SGS. Work that the finance and operations team previously handled manually for every ticket now requires significantly less effort.
Less time spent reviewing and extracting ticket data
Claude now reviews unstructured ticket, email, and notification content and extracts the relevant information into structured JSON. Both steps previously depended on the team reading through each item by hand.
Classification handled across nine lines of business
Sorting each ticket to the right line of business, and preparing data that meets that line's requirements, now happens within the automated workflow. The team's manual classification effort drops across all nine lines of business.
Downstream ERP actions prepared from each request
Preparing downstream ERP actions was the last manual step for every ticket. Claude now identifies the action each request calls for and produces the matching BOSS-NGI API payload, reducing the effort the team spends on this step.
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