AI for regulated organizations

Get AI out of the pilot and into the real workflow.

GNS-AI maps the operating workflow, identifies where AI can remove an important constraint, builds it into the real process, proves whether it creates value, and applies Decision Control when AI shapes consequential actions.

Lighthouse representing clear direction for AI
GNS-AI Ph.D. Biomedical Engineering Abbott Diagnostics Clinical and biomedical AI Creator of Decision Control Plane™
Primary market

Health plans and payers first.

Health plans first: prior authorization, utilization management, claims, member operations, and other workflows where review burden and turnaround determine whether automation creates value. Hospitals, medical devices, federal, and other regulated industries remain active markets.

Start here

Where is your AI initiative getting stuck?

Start with the problem blocking value. Then pick the next step.

Build

Requirements are clear enough

Turn a defined problem into a working AI workflow, application, agent, or integration.

Build or fix the workflow
Prove

The pilot ran. The decision is unclear

Find out whether the pilot created enough real-world value to expand.

Evaluate an AI pilot
Scale

Plan the path to scale

Move from a working pilot to architecture, scoped build, or operating rollout that fits the live workflow.

Plan path to scale
How GNS-AI works

Prioritize → Design → Build → Prove → Scale

Prioritize → Design → Build → Prove → Scale. Decision Control applies when AI-shaped work becomes consequential.

Design

Pressure-test the path

Know what must be true before the next dollar.

$3,500 | 5 business days

AI Initiative Review
Build

Put AI in the workflow

When the problem is defined, GNS-AI can take responsibility from scope through integration, testing, validation, and handoff.

Scoped Build
Prove

Test real-world value

Decide whether a pilot earned the next investment.

Pilot Efficacy
Scale

Scale what works

Expand the path that already creates operating value.

Plan path to scale
Build

What GNS-AI builds into the live workflow.

Implementation that fits regulated operations. Not demo theater.

AI systems

Applications, assistants, agents, and agentic workflows

Build or fix AI that people can run in the real operating path.

Workflow

Workflow automation

Automate the steps, handoffs, and exceptions that decide whether AI creates value.

Data

Data and interoperability

Connect the data AI needs. Denodo is a verified technology partnership for data virtualization and semantic access.

Modernization

Operational logic and modernization

Supporting work when older process or system logic blocks a useful AI path.

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.

DCP determines how the AI-shaped action should be handled next. Show Proceed · Verify · Review · Hold or escalate.

In practice

What this looks like in the real world

Different settings. The same operating problem: how much authority, verification, and human judgment the case at hand should receive.

High-consequence information

Verification before action

CNN reported that an AI-assisted intelligence error moved toward a possible military operation before specialized analysts revisited the underlying evidence.

When should stronger verification enter before an AI-shaped conclusion becomes action?

CNN Newsource / KION report

Healthcare after deployment

Changing operating conditions

FDA/CDRH highlights how changes in populations, sites, protocols, and inputs can alter AI performance after development.

When should the same AI receive different handling because its operating conditions have changed?

FDA/CDRH postmarket monitoring

Human review

Independent judgment in practice

Payer litigation and reporting have raised questions about the practical meaning of individualized human review when automated systems shape consequential decisions.

When is a human truly exercising independent judgment?

ProPublica on Cigna PxDx

Different industries, same operating question: when should AI-shaped work be allowed to move, and when should stronger verification or qualified judgment enter first?

Engagements

Engagement options

Pick the engagement that matches the decision you need now.

$7,500 fixed fee · 7 business days

AI Use-Case Prioritization

Rank which AI opportunities deserve serious investment before build spend. Includes preparation, leadership workshop, evaluation of a bounded portfolio of use cases, prioritized recommendations, and a written next-step roadmap.

Prioritize our AI opportunities
$3,500 | 5 business days

AI Initiative Review

Pressure-test an AI, automation, workflow, or data initiative before spending more.

Review an Initiative
Scoped

Scoped Build

Turn a defined problem into a working AI workflow, application, agent, or integration.

Explore Scoped Build
Scoped

Pilot Efficacy & Scale Readiness

Find out whether a pilot worked well enough to justify the next investment.

Evaluate a Pilot
From $30,000

Decision Control Assessment

Assess one important workflow before AI receives more responsibility.

See the Assessment
Next step

Bring one AI initiative or workflow. You do not need to know which engagement fits. We will identify the right next step, or tell you when there should not be one.

Bring one initiative or workflow. We will help you choose Prioritize, Design, Build, Prove, Scale, or Decision Control.