Shriram Finance
less than 3–4 hours — Onboarding Turn-Around-Time (TAT)
Independently reportedBanking & finance · Process automation · Classical ML · In production
Process automation
Exceptional Living Centers · exacare ai
Vendor-reportedHealthcareUnited StatesIn productionEnterpriseNLP
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 exacare.com (vendor self-report). Checked against the source page on 2026-09-06. 9 of 9 figures below appear on that page word for word.
The problem
Manual, time-consuming referral review process across multiple systems, leading to duplicate effort, missed details, and slow decision-making for complex patient packets.
What was deployed
- Vendor
- exacare ai
- Products
- exacare ai
- Technique
- NLP
- Build or buy
- Bought off the shelf
- Deployment
- SaaS
- Data used
- Referral packets, clinical details, insurance information, and internal tracking data from PointClickCare (PCC).
- Scale
- 10 facilities
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.
26% increaseaccepted referrals
“26% increase in accepted referrals”
Quoted word for word from the source
32% increaseconversion rate
“32% increase in conversion rate”
Quoted word for word from the source
17% increasewin rate
“17% increase in win rate”
Quoted word for word from the source
under 10 minutesreferral review time for familiar green referralsfrom 20–25 minutes
“50% reduction in referral review time for familiar green referrals”
Quoted word for word from the source
40% growthreferral growth
“40% referral growth after implementing exacare ai”
Quoted word for word from the source · round percentage, no baseline given
31% growthaverage daily census
“31% growth in average daily census across the 10 centers”
Quoted word for word from the source
494accepted referrals (volume)from 391Comparing the team's first month on exacare ai with a recent 30-day period
“accepted referrals increased from 391 to 494 (26%)”
Quoted word for word from the source
192conversion rate (volume)from 146Comparing the team's first month on exacare ai with a recent 30-day period
“conversion rate increased from 146 to 192 (32%)”
Quoted word for word from the source
65–70%offer rate on non-denied referralsfrom about 40%
“We used to offer beds on about 40% of our non-denied referrals. Now we’re up to 65–70%.”
Quoted word for word from the source
“Even when I've got quite a few referrals stacked up, I have the comfort of knowing exacare ai is working for me. I can have that laser focus on what I need to drill down on.”
Difficulties and limits
- Building buy-in across senior leadership, operations, and clinical teams
- Ensuring facility leaders trusted the platform's consistency and referral status application
- Gradual adoption by users resistant to change
Sources
- exacare.com — vendor self-report, 2026-07-02
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