Shriram Finance
less than 3–4 hours — Onboarding Turn-Around-Time (TAT)
Independently reportedBanking & finance · Process automation · Classical ML · In production
Process automation
Tryg · boost.ai
Vendor-reportedInsuranceDenmarkIn productionEnterpriseNLPLive 2018
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. 2 of 2 figures below appear on that page word for word.
The problem
Enhance support staff capacity and quality, and avoid putting customers on hold while representatives seek information from the back office.
What was deployed
- Vendor
- boost.ai
- Technique
- NLP
- Build or buy
- Bought off the shelf
- Deployment
- SaaS
- Data used
- 1,200 topics
- Scale
- 750 employees daily
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.
750employees assisteddaily
“assisting 750 Tryg employees daily at the company’s headquarters outside of Copenhagen.”
Quoted word for word from the source
95accuracy
“The virtual agent is able to provide consistently accurate assistance - answering correctly in 95% of cases”
Quoted word for word from the source
more monthly sessions with Rosa than calls to the back officeinternal sessions vs. back office callssince September 2019
“Tryg reporting that, since September 2019, they are now logging more monthly sessions with Rosa than calls to the back office.”
Quoted word for word from the source
“At Tryg, we focus on finding the right balance between human and machine. Our virtual agents have been important in communicating this to our customers.”
Sources
- boost.ai — vendor self-report
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