Shriram Finance
less than 3–4 hours — Onboarding Turn-Around-Time (TAT)
Independently reportedBanking & finance · Process automation · Classical ML · In production
Artificial intelligence, professionally covered
Process automation
Vendor-reported. The customer is named and the numbers are quoted from the source page, but the account comes from the vendor. No independent confirmation.
Reported by medius.com (vendor self-report). Checked against the source page on 2026-09-06. 1 of 1 figures below appear on that page word for word.
AP inbox received over 100 daily emails from vendors, requiring tedious, time-consuming manual replies and draining team morale.
Each row is quoted from the source. Figures we could not find on the page in those words are marked — they are kept, not deleted, so you can judge them.
“Inbox volume dropped From a multi-hour task to under 30 minutes per day”
Quoted word for word from the source
“Improved response time Vendors received AI updates to their inquiries in minutes instead of days”
Quoted word for word from the source
“Inbox clutter was gone / Now that AI was handling the basic invoice checks, the AP team focuses on strategic issues”
Not found on the source page in these words
“Measurable decline in escalations”
Quoted word for word from the source
“I thought the biggest benefit would be time savings, but really, it was the team engagement. They were excited, energized, and curious in a way we don’t always see in AP.”
less than 3–4 hours — Onboarding Turn-Around-Time (TAT)
Independently reportedBanking & finance · Process automation · Classical ML · In production
Independently reportedManufacturing · Process automation · Classical ML · Scaled
under 10 minutes — Time for root cause analysis
Independently reportedManufacturing · Process automation · AI agents · In production
88% — autonomous IT resolution rate
Independently reportedTechnology & software · Process automation · NLP · Scaled
10% more — shopper spend
Independently reportedRetail & e-commerce · Process automation · Computer vision · Scaled · 2024
increased by 15% — accuracy
Independently reportedInsurance · Process automation · Classical ML · Scaled · 2019