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 scalify.au (vendor self-report). Checked against the source page on 2026-09-06. 2 of 2 figures below appear on that page word for word.
A two-person industrial coatings business struggled with administrative tasks like support, quoting, follow-ups, and scheduling, limiting growth and diverting owners from core work.
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.
“Around 70% of routine enquiries are handled end to end by the AI team”
Quoted word for word from the source
“all without a single extra hire.”
Quoted word for word from the source
“Shimicoat reached and holds seven-figure revenue with a team of two”
Quoted word for word from the source
“support is faster”
Quoted word for word from the source
“no quote goes un-chased”
Quoted word for word from the source
“the schedule stays in order”
Quoted word for word from the source
“There are two of us, and the AI team is the reason that works. Support, quoting and follow-ups happen while we are in the workshop.”
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
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