Shriram Finance
less than 3–4 hours — Onboarding Turn-Around-Time (TAT)
Independently reportedBanking & finance · Process automation · Classical ML · In production
Process automation
DNB · boost.ai
Vendor-reportedBanking & financeNorwayScaledEnterpriseNLPLive 2020
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 boost.ai (vendor self-report). Checked against the source page on 2026-09-06. 3 of 3 figures below appear on that page word for word.
The problem
Customer service agents struggled to quickly and accurately access routines from an inefficient, time-consuming document management system.
What was deployed
- Vendor
- boost.ai
- Products
- boost.ai platform, Juno (virtual agent)
- Technique
- NLP
- Build or buy
- Bought off the shelf
- Deployment
- SaaS
- Data used
- routines - processes outlining how they complete a procedure or answer a query
- Scale
- 7 business units across Private and Corporate Banking, 3,400+ topics covered
What changed
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.
1,200Daily active users
“With around 1,200 daily active users, Juno answered over 2 million questions in 2022 alone”
Quoted word for word from the source
2 millionQuestions answeredin 2022 alone
“With around 1,200 daily active users, Juno answered over 2 million questions in 2022 alone”
Quoted word for word from the source
80,000Conversations per monthper month
“Juno handles an average of 80,000 conversations per month”
Quoted word for word from the source
“Juno has been a game-changer for our customer service agents. It has made it a lot easier to find information, making their jobs easier and customers receive faster and more accurate responses to their inquiries.”
Sources
- boost.ai — vendor self-report
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