AI & Agentic Systems

From AI assistants
to AI workforces.

UIT builds AI systems for healthcare that are assistive by default. Generative AI, copilots, and conversational agents support people at the point of work. Autonomy is introduced only within tightly scoped, well-defined operational tasks — never for clinical decisions — and every agent operates with human oversight, an escalation path, and an audit trail behind it.

Core building blocks

The vocabulary behind every UIT AI system

Nine components, combined differently depending on the workflow — from a single assistive copilot to a coordinated multi-agent operation.

Generative AI

Foundation models tuned for healthcare language — drafting documentation, summarizing records, and generating structured content for a qualified person to review before it's used.

Conversational AI

Natural-language interfaces that let patients ask about their care plan and let staff query operational or clinical data in plain language, with every exchange logged.

AI Copilots

Assistive tools embedded directly inside coding, scheduling, and documentation workflows — surfacing a suggestion that a person accepts, edits, or rejects.

Multi-Agent Orchestration

A coordination layer that lets specialized agents hand off work to one another — a billing agent flags an issue, a revenue agent routes it — without any agent acting outside its defined scope.

AI Memory

Persistent, structured context — prior interactions, case status, patient history — so an agent reasons with continuity across a workflow instead of a single isolated prompt.

Knowledge Graphs & Knowledge Systems

Structured representations of clinical, payer, and operational knowledge that ground every agent response in your organization's actual policies and data.

Workflow Intelligence

Pattern recognition across administrative and operational workflows — identifying bottlenecks, prioritizing queues, routing tasks — so teams spend less time on triage.

Autonomous Operations (bounded, governed)

A narrow set of well-defined, low-risk tasks — re-running a report, updating a status, routing a queue item — that agents complete without a per-step trigger, inside limits your team sets and can audit.

Human-in-the-Loop Governance

Approval checkpoints, escalation paths, and override controls built into every agent workflow, so a person remains accountable for every consequential decision.

Product · Conversational AI

Nuvia AI — the conversational layer for patients and care teams

Nuvia AI is the applied expression of the conversational and generative building blocks on this page. It helps patients understand their care plan, helps staff query operational and clinical information in plain language, and drafts documentation for a clinician or administrator to review. It answers and assists — it does not make clinical decisions.

  • Patient-facing conversational support
  • Staff-facing natural-language queries
  • Documentation drafting for human review
  • Every conversation logged and auditable
Who talks to Nuvia AI
PatientsCare TeamsAdministrative Staff

Nuvia AI

Conversational healthcare intelligence — answers, drafts, and assists

A person reviews and acts

Clinical and consequential outputs always route to a human

Product · Agent Orchestration

Quantum AgentOS — the operating layer that runs the agent workforce

Quantum AgentOS is where the multi-agent orchestration and governance ideas on this page become an operating system — assigning work to specialized agents, enforcing the boundaries each one runs within, and routing anything that requires judgment to a person. It's the coordination layer beneath every specialized agent described below.

  • Multi-agent task assignment & coordination
  • Defined operational boundaries per agent
  • Built-in escalation to human reviewers
  • Full activity logging & audit trail
What Quantum AgentOS coordinates
Population HealthRevenueOperationsGrowthFinanceMarketing

Quantum AgentOS

Assigns, bounds, and audits every agent's work

AI workforce architecture

How data becomes a governed action

Six stages, one architecture — from raw data to an action a person takes, with oversight built in at every step.

01

Data & Context

Clinical, operational, financial, and patient-generated data that grounds every agent.

02

Knowledge & Memory

Structured knowledge systems and persistent memory that keep reasoning consistent.

03

Agent Orchestration

Quantum AgentOS assigns tasks and enforces each agent's operating boundaries.

04

Specialized Agents

Purpose-built agents executing defined tasks across clinical, revenue, and growth functions.

05

Human Oversight & Governance

Checkpoints and escalation paths that keep a person accountable for judgment calls.

06

Action

A task completed or a decision made by a person, with a full audit trail behind it.

The agent roster

Ten specialized agents, each with a defined scope

Every agent below is scoped to a specific operational function, runs inside limits set by your team, and escalates anything requiring judgment — clinical, financial, or otherwise — to a person. None holds clinical decision-making authority.

Population Health Agent

Surfaces risk and care-gap signals across a patient population for care teams to act on.

Clinical Intelligence Agent

Summarizes and structures clinical information to support, not replace, clinician review.

Revenue Intelligence Agent

Flags coding, claims, and denial patterns for billing teams to investigate and resolve.

Value-Based Care Agent

Tracks quality measures and risk-adjustment data against program requirements.

Executive Intelligence Agent

Rolls up operational and financial signals into leadership-ready summaries.

Operations Agent

Automates scheduling, task routing, and administrative workflow steps.

Growth Intelligence Agent

Tracks pipeline, engagement, and market signals for business development teams.

Finance Agent

Reconciles financial data and flags anomalies for finance staff to review.

Marketing Agent

Drafts and coordinates content and campaign workflows for marketing teams to approve.

Partnership Agent

Tracks partner and vendor relationship data, renewal timelines, and integration milestones.

Responsible by design

Governance built into the architecture, not bolted on after

Every agent on this page operates inside the same governance framework, regardless of how routine the task looks.

Human-in-the-Loop Checkpoints

Any workflow with clinical, financial, or patient-facing consequence routes through a defined approval or review step before action is taken.

Bounded Autonomy

Agents complete only the specific, well-defined tasks they're scoped for — nothing broader, and nothing clinical, without a human decision in the loop.

Audit Trails

Every agent action, recommendation, and escalation is logged, timestamped, and reviewable after the fact.

Explainability

Agent outputs are traceable to the data and logic behind them, so a reviewer can understand why a recommendation was made.

Escalation Paths

When a task falls outside an agent's defined scope or confidence threshold, it's routed to a person, not resolved silently.

Access Control & Security

Role-based access, encryption, and the same security discipline applied to every other system in your environment.

This page describes how we design agentic systems. For the complete policy governing how we build, test, and deploy AI at UIT — including the boundaries we place on clinical use — read our responsible AI approach.
Common questions

About agentic AI at UIT

Does AI make clinical decisions on its own?
No. Every clinical-adjacent capability on this page is decision support — it surfaces information, drafts, or flags for a clinician or qualified staff member to review and decide. We do not deploy AI for autonomous clinical decision-making.
What does "bounded autonomy" actually mean?
It means an agent can complete a small set of clearly defined, low-risk operational tasks — like updating a status or generating a routine report — without waiting on a person for each step. Anything outside that defined scope, or involving clinical or high-stakes judgment, escalates to a person.
How is agent activity audited?
Every agent action is logged with enough context to reconstruct what happened, when, and why — the data it used, the output it produced, and whether a human reviewed or overrode it.
Can Quantum AgentOS integrate with our existing systems?
Yes — it's designed to sit alongside your existing EHR, claims, and operational systems through our interoperability layer, not to replace them.
Where can I read the full responsible AI policy?
See our responsible AI approach for the complete policy governing how we design, test, and deploy AI systems.

Ready to put agentic AI
to work — safely?

Tell us about the workflow you want to augment or automate. We'll show you where automation fits and where a human should stay firmly in the loop.