How We Work
AI handles the volume. We handle the judgment. You handle the decisions that are yours.
Three ways to engage — from learning the model yourself to having us run it for you. The division of labor is the same at every tier.
The Division of Labor
Who does what
Every engagement — regardless of tier — follows the same model. AI handles the volume. We handle the judgment. You handle the decisions that are yours.
AI handles the volume
- Gathers context from your systems
- Produces the first draft of every deliverable
- Flags edge cases it cannot resolve
- Runs quality checks before anything leaves the queue
- Maintains a complete audit trail
We handle the judgment
- Reviews every AI output before it reaches you
- Applies domain expertise to flagged and ambiguous cases
- Rejects work that doesn't meet the bar — it goes back, not forward
- Makes the calls that require 28 years of operations experience
- Takes responsibility for what gets delivered
You handle what's yours
- Approves or redirects deliverables in the portal
- Provides context only you have
- Makes organizational decisions
- Never touches the repetitive prep work
You get the output of AI agents and a specialist with 28 years in operations. You only see work that's already been reviewed.
Three ways to work together
Learn + Build It Yourself
You become the human in the loop for your own org.
The workshop teaches the five HITL pillars in 90 minutes. You walk away with a governance canvas and open-source patterns. You configure Nod and Mahoosuc.ai. You run your own approval gates. We give you the model — you apply it. You leave the workshop as the practitioner for your own systems.
View Workshop ScheduleManaged Build
We are your human+AI team. You approve outputs, not process.
A 4–8 week engagement where we embed in your workflow. AI handles the volume. We review every output and take responsibility for what gets delivered. You approve in the portal and make the organizational calls. A typical week: AI runs the tasks. We review. You approve in the portal.
Get a ProposalContinuous Governance
We manage your AI systems as your org evolves.
Retained partnership with monthly reporting and quarterly discipline reviews. As your goals and constraints shift, the Nod and Mahoosuc.ai configurations shift with them. We track Trust Velocity and Correction Ratio on your behalf. As your goals change, the system changes. We track the metrics so you don't have to.
Discuss PartnershipThe AI layer signals before it acts
Before any output reaches a specialist for review, the AI layer emits three structured signals. This is the cooperation layer — built into every workflow at every tier.
Every AI output carries a score from 0–1. Low confidence routes to human review automatically.
The AI states what it is taking for granted. Reviewers see the reasoning, not just the answer.
When the AI disagrees or is uncertain, it flags it — mild, strong, or blocking — before anything executes.
Specialists review the signal alongside the output. You approve the outcome. Nothing executes without this loop completing.
A Worked Example
Prior auth backlog, healthcare ops team
50 prior auth cases. Here's how the work moves through the system.
Submit task in the portal: "Process this week's prior auth queue"
Pulls patient records, fills standard form sections, flags 7 cases with missing data
Reviews all 50 cases. Approves 43. Returns 7 flagged cases with specific remediation notes
Applies practitioner notes, regenerates the 7 flagged cases
Reviews revised cases. Approves 6. Escalates 1 for your decision
Reviews the single escalated case and makes the clinical judgment call
Submits to payers. Audit trail complete.
You made one decision. We made six. AI handled the rest.
Ready to see how this works for your team?
Start with a 30-minute scope call. Walk me through your biggest workflow friction — I'll tell you which tier fits, what the division of labor looks like for your specific case, and what it would take to build.