The cost
Too much review wastes automation. Too little control takes too much risk.
Decision Control Plane™
A model can work correctly and the final action can still be wrong.
Decision Control Plane™ controls what happens when AI-shaped work becomes a consequential action. It helps regulated organizations get more useful automation, keep responsibility selective, and keep a clear record of why an action was allowed.
DCP
The problem
Correct model output is not the same as a safe final action.
AI can draft, rank, route, or recommend well and still push the wrong action into a live workflow. Review grows. Value leaks. Leaders cannot explain why AI was allowed to act on a hard case.
The better state
Give AI more room where the case supports it. Add control where consequence and uncertainty rise. Keep a clear record.
Human authority stays
Organizational policy and qualified decision-makers keep final decision authority. DCP controls how AI-shaped work is handled before the action lands.
What changes
Outcomes Decision Control is built to create.
Enterprise decision-control for regulated environments.
More useful automation
Let AI finish more work where the case supports it.
Selective responsibility
Expand AI work only where operating evidence supports it.
Stronger control
Add tighter handling when consequence, uncertainty, or policy demand it.
Lower unnecessary review
Stop reviewing every case the same way.
Clearer accountability
Know who owned the handling decision for the action.
Better economics
Count review, delay, exceptions, and failure cost at the unit of work.
Preserved record
Keep why an action was allowed under the conditions that existed.
Public actions
Four ways a case can move.
Same workflow. Different handling by case. A record you can explain.
Proceed
Let the AI-shaped action move forward when conditions support it.
Verify
Confirm sources or workflow facts before reliance grows.
Review
Require a qualified person to review before the action moves.
Hold or escalate
Pause the action, or send it to higher authority, until required conditions are met.
Buyer questions
Three questions Decision Control answers.
Use these when AI already shapes consequential work.
Where is AI still creating value?
After review, exceptions, delay, and failure cost are counted.
Where can AI take on more work?
Where operating evidence supports more AI responsibility.
Can you explain why AI was allowed to act?
Knowing a model ran is not the same as defending the action.
How to start
Begin with a Decision Control Assessment.
One consequential workflow. Public terms: 3-4 weeks | Starts at $30,000.
Bounded assessment
Find where AI can do more work, and where a person still needs to step in.
Shadow Mode
Observe how Decision Control would evaluate an existing workflow before you change live handling.
Then control
Move to persistent Decision Control when the operating case justifies it.
Illustrative example
AI-shaped action about to post
Hold or escalate
Situation
An AI score and system checks support a high-dollar claim denial. The denial is ready to post. A qualified person has not confirmed it yet.
Handling result
Hold the denial and send it to a qualified reviewer before it posts.
Buyer value. Leaders can show what was stopped, who must review it, and what happens next.
Shadow Mode first.
Shadow Mode shows where Proceed, Verify, Review, or Hold or escalate would have applied, without changing production yet.
Buyer value
Different systems answer different questions.
Use the right control layer for the job.
Workflow automation
Moves work through steps and handoffs. It does not decide how much authority AI should receive on a consequential case.
Model monitoring
Tracks model quality and drift. It does not set case-level handling when the final action still has to land safely.
Policy governance
Sets rules, roles, and oversight. It often sits above the runtime moment when AI-shaped work becomes an action.
Decision Control
Controls what happens when AI-shaped work becomes a consequential action: proceed, verify, review, or hold, with a record you can explain.
Discuss a Decision Control Assessment
Bring one consequential workflow. We will confirm where AI can do more work, where a person still needs to step in, and whether persistent Decision Control belongs.