Clinical Operations Exception Monitoring
A healthcare operations team reduced SLA breach detection from T+48 hours to T+2 hours — without a single engineering sprint after initial setup.
T+48h → T+2h
SLA Breach Detection
19 days
Time to Live
Zero
Engineering Dependency
The Situation
A healthcare operations team managing clinical site performance had patient encounter data in one system, site SLA commitments tracked in a separate database, and weekly compliance reports uploaded as files by site coordinators. There was no unified view. SLA breaches — delayed reports, missed documentation windows, threshold crossings — were typically discovered during the weekly review call, 48–72 hours after they occurred. Compliance management required a traceable chain from detected exception to documented resolution, which manual processes could not reliably provide.
Data sources
Patient Encounter System
Clinical site activity data
SLA Commitment DB
Site-level contracted thresholds
Site Coordinator Files
Weekly compliance uploads
Manual ops process
Failure events
The Approach
Connect your sources
Patient system, SLA database, and coordinator file uploads connected — read-only, 19-day setup.
Configure SLA rules per site tier
Documentation windows, escalation thresholds, and breach definitions written in plain language.
Autonmis monitors continuously
Automated evaluation runs on schedule. Breaches surface in 2 hours with full traceable chain.
After
Patient Encounter System
Clinical site activity data
SLA Commitment DB
Site-level contracted thresholds
Site Coordinator Files
Weekly compliance uploads
Autonmis
Governed Intelligence Layer
Knowledge Base
rules · thresholds · logic
Connected to all three source types. The Knowledge Base was configured with SLA definitions, documentation window rules, and escalation thresholds specific to each site tier. Autonmis ran automated cross-source evaluation on a schedule, comparing actual site performance against contracted SLA thresholds and flagging exceptions before they became compliance events. Exception briefs were delivered to the ops lead each morning. When a threshold crossing occurred during the day, a Slack alert fired with the site, the specific SLA dimension, and the time elapsed since the breach. The lifecycle governance layer — draft → review → approved on every published analysis — meant every exception report that reached a compliance officer had been formally reviewed and promoted.
Results
T+48 hours → T+2 hours
SLA breach detection
Previously found at weekly review call
~70% reduction
Weekly compliance prep time
Exception reports generated and reviewed automatically
Day one
Traceable exception-to-resolution chain established
Every breach has documented detection and resolution
Zero
Engineering dependency post-setup
Ops team manages rules and thresholds independently
19 days
Time to first live exception alert
From initial source connection to production monitoring
Implementation
Time to live
3 weeks
Sources connected
3
Engineering dependency
Zero
Ready to see it in your stack?
We can scope your use case to a live workflow
in the first session.
Three sources. No engineering dependency. First automation in under three weeks.
Book a 30-minute callContinue reading
Other case studies
See how other operations teams have deployed agentic intelligence across industries.
Collections Exception Intelligence
A mid-market NBFC eliminated 90 minutes of daily manual reconciliation and reduced exception discovery lag from 14 hours to under 2 minutes.
Read case study QSR & RetailCampaign ROI Intelligence for Multi-Location Operators
A large franchise operator replaced weekly manual campaign reporting with a live cross-source dashboard — from raw sources to executive brief in 21 days.
Read case study Voice AI WorkflowsAutomated Quality Governance for AI Training Data
A voice data operation replaced manual QC review with a 7-stage automated evaluation pipeline — routing 11 submissions per evaluator-hour, with full audit provenance for every decision.
Read case study