Prove What AI Is Delivering From Your Workflow Data
Your AI vendor says they're saving you time and money. But that number comes from their dashboard, not yours. Operon gives you the independent operational evidence.
Built for health plans and the clinical operations teams running them.The Problem
You don't know which cases AI actually touched.
AI "runs" in your workflows, but your systems don't tag which cases were AI-handled, human-handled, or hybrid. Without that tagging, everything downstream - cost comparison, time comparison, ROI calculation - is impossible. You're measuring AI impact with no idea where AI was involved.
You have no operational baseline for "before AI."
You can't measure improvement without a starting point. Cost per case before AI, cycle time before AI, touch count before AI - this data was never captured. So the before/after comparison your CFO is asking for doesn't exist. Every "savings" number is an estimate built on assumptions.
Vendor-reported savings are not your savings.
Your AI vendor's dashboard shows model throughput, uptime, and accuracy. Those metrics describe the model - not your operation. The question is whether the operation improved: did the case move faster? Did it cost less? Did the human still have to intervene? That requires your workflow data, not theirs.
Why This Can't Wait
94% adopted, ~5% can prove it: boards demand ROI evidence
Payer-side AI spending remains just $50M against $1.4B total healthcare AI spend. Boards and CFOs are demanding ROI evidence before expanding budgets.
State AI transparency laws effective January 1, 2026
Texas TRAIGA and California transparency law require documenting and disclosing AI governance, including operational impact. Measurement infrastructure is now a compliance requirement.
Accreditation pressure: first comprehensive AI adoption guidance released
Joint Commission and Coalition for Health AI released guidance for responsible AI adoption (September 2025). Plans without documented AI impact measurement risk audit findings.
Prove the Saving, Case by Case
Operon tags every case by handler type - AI-only, human-only, or hybrid - and captures the operational baseline your CFO needs. Cost per case, cycle time, touch count, before and after AI. Measured from your workflows, not your vendor's dashboard.
AI Adoption Mix
You can't measure AI impact if you don't know where AI is involved. Adoption Mix tags every case by handler type and shows how the mix is shifting over time, by workflow. The foundation for every ROI conversation that follows.
ROI Impact Explorer
Your CFO wants before vs. after. This view delivers it - baseline cost and cycle time compared to actuals, with dollars saved and hours saved per case. Measured from your workflow data, not an estimate built on vendor assumptions.
Human vs. AI Comparison
Same workflow, same case type - how do AI-handled cases actually perform against human-handled ones? Side-by-side comparison with real data. No vendor estimates, no model accuracy scores. Operational outcomes only.
Cost & Time Efficiency Leaders
Not all AI investments deliver equally. This view ranks which AI-powered interactions save the most dollars and time, and shows their contribution to overall ROI. Know which ones to scale and which ones aren't moving the needle.
How It Works
Connect
Read-only integrations with your workflow systems. Tag every resource as human, AI, or automated to create the baseline.
See
AI impact dashboards live in 2-4 weeks. Adoption trends, cost comparisons, and ROI evidence from your operational data.
Act
Walk into your next budget review with independent proof. Scale what works, fix what doesn't, and make AI investment decisions based on evidence.
See It on Your Own Cases
30 minutes with our team. We'll look at the workflow you run today and show what Operon would surface in the first weeks.