Shriram Finance
less than 3–4 hours — Onboarding Turn-Around-Time (TAT)
Independently reportedBanking & finance · Process automation · Classical ML · In production
Process automation
VreonTech · Cimplify.AI
Vendor-reportedOtherIndiaIn productionComputer vision
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 cimplify.ai (vendor self-report). Checked against the source page on 2026-09-06. 6 of 6 figures below appear on that page word for word.
The problem
Manual image processing for AR/VR content was time-consuming, costly, and created production bottlenecks, eroding project margins.
What was deployed
- Vendor
- Cimplify.AI
- Technique
- Computer vision
- Build or buy
- Bought off the shelf
- Deployment
- Custom build
- Data used
- VreonTech's own image library
- Scale
- 1,000+ images processed per week
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.
$0.10Per-image costfrom $10
“cutting per-image costs from $10 to $0.10”
Quoted word for word from the source
3 secondsPer-image processing timefrom 2 hours
“processing time from 2 hours to 3 seconds”
Quoted word for word from the source
Productivity
“500% Productivity Gain”
Quoted word for word from the source · round percentage, no baseline given
five times the project loadProject load capacity handled by same team
“The same team now handles five times the project load”
Quoted word for word from the source
95%+Model Accuracy on AR/VR-specific image types
“Model Accuracy 95%+ on AR/VR-specific image types”
Quoted word for word from the source
Zero quality compromisesQC Pass Rate
“QC Pass Rate Zero quality compromises vs. manual process”
Quoted word for word from the source
Difficulties and limits
- Skilled designers spent 2-3 hours per image on background removal, a repetitive task consuming creative capacity that should have been directed toward innovation.
- Outsourced background removal reached $10 per image; at 1,000+ images weekly this cost structure was directly eroding project margins and competitive positioning.
- The weekly volume of 1,000+ images created severe pipeline bottlenecks, delaying AR/VR content delivery and limiting the company's ability to take on new projects.
- AR/VR and XR applications demand pixel-perfect image isolation; any degradation in output quality would undermine the immersive experience and brand reputation.
- Automated QC flags edge-case images for human review before delivery, rather than shipping 100% touchless output.
Sources
- cimplify.ai — vendor self-report
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