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 amazon.com (vendor self-report). Checked against the source page on 2026-09-06. 3 of 3 figures below appear on that page word for word.
Financial services organizations are weighed down by repetitive manual work, lack capacity to build AI, and need to verify AI outputs with mathematical certainty.
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.
“reducing manual cross-referencing from 2 weeks to 30 minutes without sacrificing rigor.”
Quoted word for word from the source
“New client accounts that required 3–4 hours of retyping data across custodian, CRM, and compliance systems now open and verify in 10 minutes.”
Quoted word for word from the source
“Marketing and social media posts that sat in a 3-day review queue for SEC/FINRA compliance now clear in 30 seconds.”
Quoted word for word from the source
“LLMs give us the flexibility to understand any business process. Automated Reasoning checks on AWS give us the rigor to prove the output is correct. That’s what makes this work in a regulated industry.”
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