The problem, the system, the result.

The problem

Dispatch ran through a single ops desk that drowned at peak. Late-route reassignments were manual, slow, and routinely cost the on-time guarantee.

The system

Built a live routing-intelligence layer that scores every active route for risk and recommends reassignments before a delay compounds — dispatcher makes the final call.

fewer late deliveries, first quarter live

31%fewer late deliveries, first quarter live

The problem

Finance closed the books eleven days late every month. Reconciliation lived in spreadsheets and three people's heads, stale before leadership saw it.

The system

Automated the entire reconciliation and reporting pipeline end-to-end, with self-checking validations and an exception queue for cases that genuinely needed a human.

days to close the month

11→2days to close the month

The problem

Patient intake and referral coordination differed at every clinic. The inconsistency showed up as wait times and lost referrals.

The system

Rebuilt intake as one operating system across all sites — standardized SOPs, a shared metric set, automated referral routing — then trained the leads and handed it back.

faster referral turnaround across the network

40%faster referral turnaround across the network

The problem

Support volume scaled faster than headcount. Response times slipped, the same hundred questions consumed the queue, no time left for cases that mattered.

The system

Deployed an AI resolution layer that handles routine tickets end-to-end and routes the rest with full context attached, so agents open every conversation already informed.

of tickets resolved without a human touch

68%of tickets resolved without a human touch