AI that earns its place in the workflow.
Healthcare doesn't need one more demo-grade model. It needs intelligence that is correct, explainable, and embedded where the work actually happens. That's how we think about AI at Neutrino.
Graduated intelligence — the simplest mechanism that works
We choose the lightest-weight mechanism that produces a reliable outcome. We compose them. We instrument every step.
Deterministic where absolute correctness and auditability matter. Often the right answer — not the outdated one.
Supervised models where patterns are stable, labeled data exists, and generalization is the goal.
Language-heavy work — policy interpretation, document assembly, summarization — with grounding and guardrails.
Critical junctures stay human — with system-assisted context, not system-made decisions.
Hub AI is the intelligence layer
Under every AccessHub app — Intake, Case Intelligence, Access Intelligence, Affordability, Field, Channel, Finance, Governance, HCP Portal — Hub AI provides shared intake, risk, NBA, copilot, data-quality, and HITL services with a central model registry and prompt studio.
Intelligence where the work is
AI doesn't live in a separate console. It surfaces inside the tools your teams already use — or next to them via sidecar.
Copilots suggest next-best actions inside hub and SP workflows — agents stay in control.
Drafting PA inside the clinical flow — no extra portal to log into.
Operational signals surfaced to the people who can change policy, not just watch it.
From Copilot to Autonomous: the next evolution of Patient Access.
AI agents that assist, orchestrate, and act — within strict healthcare guardrails. Not a replacement for the ecosystem's actors — an accelerator for them.
What Agentic AI is — and isn't
Agentic AI extends the AI Layer into scoped action. It doesn't replace hubs, SPs, providers, or payers — it helps the ecosystem operate with more precision, speed, and intelligence.
- Assistive and orchestrative — works alongside your people, not around them
- Operates within explicit boundaries set by the program
- Acts on high-confidence, repeatable workflows
- Escalates uncertainty — always
- Not a fully autonomous system
- Not a replacement for hub, SP, provider, or payer roles
- Not a black box — every action is explainable and auditable
- Not one-size-fits-all — every agent is configured by program and payer
Insight → Copilot → Agentic
We don't deploy autonomy on day one. We earn it — through instrumentation, human review, and measured expansion of scope.
Surface patterns, risks, and recommendations — humans decide.
Draft, assemble, or pre-populate work — humans review and approve.
Execute bounded actions within policy — full lineage, review, and revert.
- Confidence thresholdsAgents act only when scoring crosses program-defined confidence bars.
- Rule constraintsEvery action is bounded by explicit policy and program rules.
- Audit logsEvery decision, input, and output is logged with full lineage.
- Role-based permissionsWhich agents can run where, and for whom, is governed centrally.
Agents, built for Patient Access
Each agent is scoped to a specific job — with its own guardrails and escalation rules. Click a tile for detail.
Built for healthcare guardrails
We treat AI governance like product surface area — not paperwork.
Humans are present at every consequential decision — system-assisted, not system-replaced.
Every agent action is logged, explainable, and reviewable after the fact.
Thresholds, scope, and escalation rules are configured per program and payer.
Agents don't act outside defined boundaries — ever.
Our Agentic AI does not replace the ecosystem — it enables it to operate with precision, speed, and intelligence.
Talk to our team about piloting an agent in a scoped, low-risk workflow — with thresholds, review, and revert built in from day one.