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“Ella has completely changed how we handle emailed and faxed orders. It’s saving hours of time every day for my team.”
The challenge
Manual order entry consuming half the workday
Before Ella, Howard Elliott’s customer service team spent a large portion of every day manually entering orders. Purchase orders arrived in many formats, sometimes as attachments, sometimes written directly in email bodies, and occasionally missing key details.
Each order had to be reviewed carefully to confirm customer records, pricing, ship-to addresses, and item details. This process took three to four hours every day and pulled the team away from higher-value customer service work. Errors were an ongoing risk, especially when pricing or address information was outdated.
“Manually entering emailed and faxed orders was tedious and took time away from serving customers.”
The turning point
AI order entry instead of human retyping
Howard Elliott adopted Ella, AI order and quote automation assistant, to remove manual re-entry from the order workflow. Instead of deciphering emails and PDFs line by line, the team now forwards orders directly to Ella with minimal guidance when needed.
Ella processes the order, extracts line items, validates customer and pricing data, and surfaces the order inside WizCommerce for quick review. What once took hours of manual work is now reduced to a short verification step before the order flows into the system.
“Ella processes orders in about 15 minutes, sometimes even faster, and they show up right in our dashboard.”
Results
Hours reclaimed and errors eliminated
With Ella in place, Howard Elliott reduced order entry time from three to four hours per day to a matter of minutes per order. Reviewing an AI-processed order now takes around five minutes, freeing the customer service team to focus on customer communication instead of data entry.
Ella also flags discrepancies automatically. Pricing mismatches, incorrect addresses, and missing details are surfaced before orders move forward, eliminating the order entry mistakes that previously required follow-ups and corrections.
The result is a faster, cleaner order flow that scales without adding headcount.
“We’re not seeing order entry errors anymore because the human entry isn’t there.”
