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 yuno.to (vendor self-report). Checked against the source page on 2026-09-05. 4 of 4 figures below appear on that page word for word.
Manual invoice reconciliation, slow and costly space visualization for proposals, and disorganized multi-catalog product data leading to wasted time searching.
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.
“The CEO was spending 10 to 15 hours every month manually reconciling invoices.”
Quoted word for word from the source
“15 hrs Recovered per month for the CEO”
Quoted word for word from the source
“Each space took 4 to 8 hours to render”
Quoted word for word from the source
“90% Less time searching product info”
Quoted word for word from the source · round percentage, no baseline given
“YUNO didn't just automate tasks — they removed entire bottlenecks from our operation. I got my time back, my team moves faster, and our proposals now look like they come from a firm ten times our size.”
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
88% — autonomous IT resolution rate
Independently reportedTechnology & software · Process automation · NLP · Scaled
under 10 minutes — Time for root cause analysis
Independently reportedManufacturing · Process automation · AI agents · In production
increased by 15% — accuracy
Independently reportedInsurance · Process automation · Classical ML · Scaled · 2019
10% more — shopper spend
Independently reportedRetail & e-commerce · Process automation · Computer vision · Scaled · 2024