Review labor
Requester, reviewer, and approver minutes spent per decision.
- Today
- $18,659/mo
- Governed
- $8,811/mo
$9,848/mo recovered
Close-stage economics
If one execution-certainty workflow does not pay back in 60 days, it should not deploy
Choose the workflow you are evaluating, enter your own assumptions, and watch the approval drag, governed state, and payback respond as you type. If the model clears the 60-day bar, take it into an assessment; if it does not, this page says so.
No account needed — the model runs in your browser. Start from a preset profile, then replace the defaults with your own workflow numbers.
Model: AI-agent report triage · preset defaults
Edits apply instantly — the outcome panel updates as you type.
Step 2 · Enter your assumptions
Your workflow
Your modeled outcome
AI-agent report triage and action gating
Passes the 60-day test
Estimated payback
24 days$50,924 realized in 60 days against $20,138 of deployment cost.
Current drag$92,235 / month
Governed state$43,735 / month
60-day realized benefit$50,924
Deployment cost$20,138
Time to decision4.5d → 1.9d
Step 4 · Read the verdict
This workflow clears the 60-day bar
Modeled drag of $92,235 per month falls to $43,735 under governed execution. The $50,924 realized in the first 60 days covers the $20,138 deployment cost in 24 days.
We check these assumptions against one real workflow, then point you to the Sandbox or Shadow Mode, with your model attached, not a blank intake form.
Economic drivers
Where the drag comes from
These four buckets sum to the $92,235 monthly drag in your result. Each one responds to the inputs above.
Approval delay
Value at risk eroding for every day a decision waits.
- Today
- $30,556/mo
- Governed
- $12,833/mo
$17,723/mo recovered
Avoidable loss
Rework, concessions, and bad actions the policy gate prevents.
- Today
- $35,073/mo
- Governed
- $20,342/mo
$14,731/mo recovered
Low-signal work
Operator time consumed by items that deserve an explicit no-action.
- Today
- $7,947/mo
- Governed
- $1,748/mo
$6,199/mo recovered
Methodology
What the model assumes, and where it stops
Every figure above comes from these formulas and public assumptions. Nothing in the model is fitted to make a workflow pass.
How the figures are computed
Current drag
Review labor + approval-delay cost + avoidable loss + low-signal work, each computed per month from your inputs.
Governed state
The same four buckets after the governed review rate, cycle reduction, error reduction, and no-action capture apply.
Realized 60-day benefit
Gross monthly savings scaled by the ramp — benefits are not assumed to land at full run-rate from day one.
Deployment cost
Your Decionis plan for 60 days + internal implementation hours at your blended rate + integration cost + 60-day run cost.
Payback
Deployment cost divided by average daily realized savings. The page holds itself to a 60-day bar; 61–90 days reads as conditional.
Public assumptions
Baseline unmanaged decision cycle in the adoption model: 21 days
Plan cost default, the published Enterprise floor for 60 days: $9,998
Realized 60-day benefit ramp: month 1 35%, month 2 70% of run-rate benefit
Value bands from the current adoption model
Decision class
90-day value
DO NOTHING
$900
REMOVE CONSOLIDATE
$2,400
DELAY DECISION
$1,200
ADD ONE THING
$700
Do not overclaim universal ROI before workflow-specific data exists. The stronger close-stage claim is that Decionis creates the measurement layer: replay actions in Shadow Mode, convert results into signed evidence, then promote only the workflows that clear the payback and false-positive bar.
Status quo comparison
Approvals and logs are not execution authority
Most teams already run approvals, permissions, and audit logs. The question the model prices is whether those controls certify the action before it lands.
Approvals
Show someone clicked yes, but not whether the action had enough evidence to proceed.
Returns one allow/block/escalate verdict before execution.
ERP permissions
Show who had access, but not whether this specific action matched policy.
Evaluates the action, context, thresholds, and policy snapshot together.
Audit logs
Reconstruct what happened after the fact.
Creates a signed Decision Dossier at the execution boundary.
Human review
Can degrade into rubber-stamping when thresholds are unclear.
Routes gray-zone actions to named owners with reason codes attached.
Proof
The model is narrow so the proof can be real
One workflow with visible drag beats broad platform ROI. These are the artifacts your first workflow's numbers convert into.
Avoided loss
Prevented spend, refund abuse, fraud, bad disbursements, or unauthorized system changes.
Approval compression
Days to minutes or seconds when policy is clear and the safe path should not wait.
Audit prep reduction
Signed dossiers replace screenshot hunts, ticket archaeology, and manual evidence assembly.
Policy coverage
The percentage of high-risk actions evaluated before money moves or state changes.
An example Decision Dossier →
One decision, end to end: what was attempted, the policy that applied, the verdict and why, and the signed evidence.
Example Decision Dossier →
Generate the signed evidence artifact a governed decision produces at the execution boundary.
Evidence index →
The public record this page's claims are held against: verification, coverage, and posture.
Your model clears the 60-day bar. Put it in front of us.
Request the assessment with this model attached, or start in Shadow Mode and replay real actions against policy before anything enforces.