Shriram Finance
less than 3–4 hours — Onboarding Turn-Around-Time (TAT)
Independently reportedBanking & finance · Process automation · Classical ML · In production
Process automation
Brooklyn Museum · Decoded Futures
Vendor-reportedOtherUnited StatesScaledPublic sectorLLM
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 decodedfutures.nyc (vendor self-report). Checked against the source page on 2026-09-06. 1 of 1 figures below appear on that page word for word.
The problem
The Brooklyn Museum development team spent roughly 45 hours each month manually producing donor acknowledgement letters and fundraising reports.
What was deployed
- Vendor
- Decoded Futures
- Technique
- LLM
- Build or buy
- Built in-house or to order
- Deployment
- Custom build
- Data used
- detailed SOPs and letter templates; raw data exports
- Scale
- expanding AI beyond development, launching staff training, developing an AI policy, and identifying new opportunities across the institution
- Timeline
- 2 months
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.
45 hourshours reclaimedfrom 45 hours each monthevery month
“The team reclaimed those 45 hours every month”
Quoted word for word from the source
“Our big call to action after our participation in this program is to think about how AI can influence the Brooklyn Museum’s work.”
Sources
- decodedfutures.nyc — vendor self-report
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