Shriram Finance
less than 3–4 hours — Onboarding Turn-Around-Time (TAT)
Independently reportedBanking & finance · Process automation · Classical ML · In production
Process automation
Ground Control · FOIL
Vendor-reportedOtherUnited KingdomIn productionMid-marketNLP
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 foilai.co.uk (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
The traditional quoting process required time-intensive site visits and manual calculations, creating a critical bottleneck to scale.
What was deployed
- Vendor
- FOIL
- Products
- Intelligent Quoting app, FOIL Talent programme
- Technique
- NLP
- Build or buy
- Bought off the shelf
- Deployment
- Custom build
- Data used
- existing data, standardised services and pricing models
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.
10000hours savedannually
“10,000 hours saved annually”
Quoted word for word from the source
two daysquoting timefrom two weeks
“90% reduction in time From two weeks to two days fundamentally changes Ground Control's competitiveness and customer experience.”
Quoted word for word from the source
“When you're transforming an organisation, especially an SME, you're probably not going to have all the technical skills that you need in-house for a data and AI project.”
Difficulties and limits
- Services scattered across silos — the service catalogue had become unwieldy, full of duplications, inconsistencies, and variations
- Every site visit meant carbon emissions, working against the net-zero by 2035 goal
- Inability to innovate — without standardised data, building data science and AI models was impossible
Sources
- foilai.co.uk — vendor self-report
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