Case Study
AI-Powered Order Automation
Overview
A global medical device manufacturer processing over 50,000 B2B orders per month faced mounting inefficiencies from heavily manual order handling across fax, email, and portals. With 30+ staff dedicated to data entry and frequent delays caused by weekend backlogs, the company struggled to scale with rising demand. Sphere implemented an AI-powered order automation platform that transformed legacy workflows, dramatically cut labor costs, and unlocked sustainable growth—without expanding headcount.
Challenges
Manual, resource-heavy processes were no longer sustainable as order volumes climbed. The manufacturer faced a scalability ceiling—where growing demand meant growing headcount, driving up costs and straining operations.
24–48 hour delays on Mondays due to weekend order accumulation.
30+ staff manually handled POs from fax, email, post, and portals, leading to delays and errors.
12% of orders required rework due to mismatched customer/ERP data.
High operational costs
Labor-intensive workflows required bloated teams to manage peak volumes.
Our Solution
Sphere deployed an AI Order Automation Platform using proprietary accelerator frameworks to:
1. Automate multi-channel ingestion
AI parsed POs from any format (fax, email, scanned PDFs) into structured data.
2. Auto-match and validate
Cross-referenced customer details with ERP records in real time.
3. Flagged mismatches (e.g., outdated pricing, invalid shipping…
Flagged mismatches (e.g., outdated pricing, invalid shipping addresses) for human review.
4. Seamless ERP integration
Auto-generated spreadsheets and fed validated orders into the Order Management System.
5. Continuous learning
AI adapted to edge cases (e.g., handwritten POs) to improve automation rates.
Key Achievements
Staff shifted to handling exceptions only, reducing manual work
Orders fulfilled in 2 hours vs. 24–48 hours post-weekend.
83% fewer rework cases (12% → 2% error rate).
Preparing to automate 90% of orders by addressing edge cases with AI enhancements.
Result
By automating 75% of its order processing, the company reduced labor requirements from over 30 staff to just 8 – unlocking $750K in annual savings. Weekend backlogs were eliminated, fulfillment times improved, and the business scaled order volumes by 30% year-over-year without hiring additional personnel. The shift to AI-driven operations turned a cost center into a growth engine.
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Luke Suneja
Client Partner
