Intelligence trained on your hospital's goals, not a generic standard of care.

No two hospitals define success the same way. One is optimizing for quality of care, another for readmission rates, another for margin under a tightening budget, all while regulations shift and patient volumes swing without warning. Generic intelligence optimizes for generic benchmarks. Continual learning trains on the outcomes your hospital actually cares about, connecting operations, clinical care, and remote patient monitoring into intelligence that gets sharper with every patient it serves.

Outcomes and improvements

Summary

A 350 bed healthcare provider, part of a large chain, wanted to streamline their discharge process to:

• Reduce their outliers
• Reduce their turn around time (TAT)
• Improve discharge timing to shorten stays

Solution

Real-time intelligent Al agents, planned discharge module, data centric personalized advisory for all the roles in the organization.

Outcome

Released capacity of over 7 beds per day.

Target KPIs

9 months

Implementation of planned discharges

30%

87%

TAT for discharge excluding outliers

5:40 hrs

2:40 hrs

TAT for discharge including outliers

13:20 hrs

3:30 hrs

Outliers TAT (6 hrs)

75%

<7%

Bed Throughput (ALOS)

>4.5 days

<3.5 days

Monthly % discharge outliers (>6 hr TAT)

Monthly average TAT (including outliers)

Monthly % discharge outliers (>6 hr TAT)

Monthly average TAT (including outliers)

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