The demo-to-production gap
The pilot works in a sandbox. Nobody has designed what happens when the agent is wrong in front of a real customer, on a real deadline.
Design the workflow the pilot never had.
A 4–6 week fixed-scope engagement that decides who reviews what the agent produces, what happens when it's wrong, and how you know it's working, the design problem that determines whether an AI pilot turns into a production system.
Agentic Workflow Redesign
4–6 weeks · fixed scope
Your AI pilot works in a demo. Now someone has to figure out how it fits into the actual workflow, who reviews what the agent produces, what happens when it's wrong, how you know it's working, and who's accountable.
That's not an engineering problem. It's a design problem. And it's the one that determines whether your AI investment produces returns or produces a stalled proof-of-concept.
What you get
- Current-state and future-state workflow maps, where human judgment is genuinely required vs. where it's merely habitual
- Role redesign for every position the workflow touches, which activities stay human, which become AI-assisted, and which get delegated to agents
- Agentic workflow blueprints with AI agent placement, human-in-the-loop checkpoints, and escalation paths
- An evaluation framework for every AI-assisted decision point, measurable criteria, not a test plan
- RACI matrix and traceability diagrams for governance and audit
- A pilot action plan that bridges directly to implementation
This is the work every Skowak case study already describes, separating human judgment from deterministic process, redesigning workflows around that distinction, and instrumenting the result. Now it has a name.
Why pilots don't survive contact with production.
Undefined escalation
No one has decided who reviews the agent's output, or what specifically triggers a handoff to a human.
Governance on paper only
A RACI matrix exists somewhere. The actual day-to-day workflow doesn't follow it, because nobody redesigned the workflow to match.
What you walk away with.
A workflow both sides sign off on
Compliance and operations agree on where the agent acts alone and where a human has to see it first, in writing, not by convention.
Regressions caught early
An evaluation framework built around this specific workflow catches quality drops before your customers notice them.
A plan that goes straight to build
The pilot action plan bridges directly into implementation, no second round of scoping before work can start.
The redesign question, answered under real constraints.
Bitscopic · Federal healthcare
Calibrating how much the system should decide vs. show
In a clinical setting the question isn't whether the system can decide, it's how the system shows its work so a professional can accept or reject it. That calibration between automation and human judgment is the exact design problem this engagement solves.
- Review effort – cut by 50–80% without removing clinical judgment
- Design problem – how much to assert vs. how much to show
- Context – regulated, patient-data environment, the hard version of this problem
More questions?
The full FAQ, pricing, scope, and how the three engagement tiers fit together, lives on the Services overview.
Already have a pilot that's stuck?
If your AI pilot works in a demo but nobody trusts it in production yet, that's exactly the gap this engagement closes.