The pilot worked because the team worked around it.
Manual routing, cleanup, and exception handling may still be doing the hard part.
AI decision systems and control
Why was AI allowed to make this decision?
GNS-AI designs, builds, validates, and controls AI-enabled decision systems for consequential workflows. Most tools can explain the model output. They cannot show why it was allowed to shape the outcome, who had authority, or when the action should have been held.
Built for high-stakes work.Health systemsGovernmentRegulated enterpriseEnterprise dataWorkflow automation
The production gap
Model performance does not establish decision authority.
A workflow still needs evidence, authority, and stopping conditions.
The system sees documents, not the whole case.
A missing prerequisite can matter more than a high-confidence answer.
A score does not show who was allowed to decide.
The organization still has to explain why the action was permitted.
Three ways to begin
Buy the next decision, not an open-ended transformation.
Each engagement has a defined buyer trigger, output, duration, and commercial range.
AI Decision System Working Session
Choose the workflow, assign responsibility, and decide what happens next.
Prep plus half or full day
Typical investment: $15,000–$30,000
AI Decision System Blueprint
Define the complete human-AI decision system before implementation fragments it.
4–6 weeks
Typical investment: $60,000–$125,000
Production Assurance
Decide whether a pilot, vendor, or workflow is ready to buy, scale, redesign, or stop.
4–6 weeks
Typical investment: $45,000–$95,000
Abbott DiagnosticsApprox. $1.8M ARRLaboratory benchmarking and reporting program associated with recurring revenue.
Apricity HealthASCO-aligned triageMapped patient-reported symptoms to severity and clinic triage logic.
Federal health educationHRSA-sponsored speakerPrograms focused on accelerating cancer screening and practical AI adoption.
Third-party validationHAVI · INFORMS · DAMAInvited panels and speaking on enterprise AI, decision systems, and reliability.
Where we work
GNS-AI works where AI decisions carry real consequences.
Healthcare and payer, federal and public-sector, and enterprise and industrial workflows.
Healthcare & payers
Healthcare Decision Systems
Care, access, utilization, referral, and rehabilitation.
Explore healthcareFederal & public sector
Federal Decision Accountability
Connect mission authority, evidence, acquisition, and operational review.
Explore federal
Enterprise & industrial
Operational Continuity & Modernization
Preserve system knowledge and expose dependencies before critical change.
Explore enterprise & industrialPrior authorization
A clear test of whether an AI-supported decision can be defended.
Prior authorization brings evidence, clinical review, operational pressure, and patient consequence into the same workflow. GNS-AI helps organizations determine when a case can proceed, when more evidence is needed, and when qualified review must remain in control.
Decision Control Plane™
DCP is the product. Shadow mode is the entry path.
Observe one live consequential workflow, produce decision-level evidence, and define where AI influence should be allowed, held, escalated, or blocked.
Shadow pilot
10–16 weeksBegins at $125,000
Production
Licensed platformWorkflow-volume basedScoped separately
Lead with a real diagnostic
Is the pilot actually ready for production?
Assess before scaling.
Buyer questions
Questions that come up before the first engagement.
The answers determine whether GNS-AI is relevant and what the first piece of work should be.
What kind of AI initiative is a good fit for GNS-AI?
GNS-AI is best suited to consequential workflows where AI influences care, access, money, rights, safety, operations, or public trust. The strongest starting points have a real operating decision, an executive owner, and a problem the organization is already expected to solve.
What can an organization buy first?
The first purchase is a bounded Working Session, AI Decision System Blueprint, or Production Assurance engagement. When AI already influences a consequential live workflow, the entry path can be a DCP Shadow Pilot. Each option ends with a specific decision and defined deliverables.
Does the first engagement commit the organization to a larger program?
No. The first engagement answers a specific decision. Implementation, production deployment, or DCP licensing is scoped only after the evidence supports moving forward.
Start with the current decision
Request a scope for the decision in front of you.
Bring one workflow, the decision that must improve, and the outcome the organization needs.