Managed AI Workflow Optimization
Continuous optimization for production AI workflows so performance improves after launch instead of drifting.
Why this service
What Cortaris solves with it
Production AI workflows lose effectiveness without active stewardship. Data shifts, behavior shifts, models age. Managed Optimization secures performance and adoption over time.
Who it is for
Best-fit context
For organizations that want to operate, measure, and improve AI workflows over time.
Typical triggers
When this service makes sense
Continuous optimization for production AI workflows so performance improves after launch instead of drifting.
Performance drift
Declining adoption
Unclear KPI ownership
Scope
What is included
The work connects strategy, workflow design, governance, and implementation logic.
Performance monitoring
Issue detection
Workflow refinement
Adoption support
KPI tracking
Outcome
What becomes clearer
The focus is durable decision quality and operational follow-through.
More stable performance
Higher adoption
Continuous improvement cadence
Deliverables
Concrete deliverables
- Monthly performance and adoption reporting
- Defined issue detection with escalation paths
- Prioritized backlog of refinements and adaptations
- Adoption support plan with workflow owners
- Quarterly review with sponsors and the line
Engagement model
How an engagement unfolds
- 01 · 3 to 4 weeksSetup
Onboarding, measurement logic, observability, escalation design, and transfer of accountability.
- 02 · MonthlyRun
Continuous monitoring, issue detection, refinements, adoption support, and reporting.
- 03 · QuarterlyReview
KPI review with sponsors, backlog prioritization, and strategic adjustments.
Questions
Frequently asked
Do we need to have Cortaris build the workflow to use Optimization?
No. You can hand over existing workflows as long as they are sufficiently documented and instrumented with logging points.
How is the engagement structured commercially?
Typically a retainer with a defined scope, clearly documented KPIs, and calibrated effort per workflow.
What happens when an incident occurs?
Issue detection triggers, escalation paths activate the right stakeholders, and workflow adjustments are prioritized in the backlog or executed as emergencies.
Do you share our data with third parties?
No. Data processing follows your privacy framework. Optimization insights only feed back into the Cortaris method base in anonymized form.
How do you collaborate with our IT and architects?
Cortaris involves IT and architecture leaders from day one. Platform decisions, data security, and integration patterns are shared rather than bolted on.
How is the engagement structured commercially?
Clear fixed-price or sprint models for strategy and assessment phases, time-and-material or fixed price for build, retainer for optimization. Scope and expectations are documented.
Which roles do we need to provide?
At minimum a workflow owner, an IT architecture lead, and a governance stakeholder. Sponsor and line leadership decide adoption.
Next step
Start with a clear, low-risk next step.
We assess which workflows are commercially relevant, technically feasible, and operationally realistic.