Nona AI designs and implements custom AI agents for medical and healthcare companies — built around the clinical and operational workflows, EHR and claims systems, and team you already have.
Built for healthcare data sensitivity.
5.0 / 5 on TrustPaaS
We help medical and healthcare companies turn AI from scattered tools into operating capability — strategy plus implementation under one roof, built around the workflows you already run.
We do not just plan. We map clinical and operational workflows, design AI roadmaps, build the agents, integrate the systems, train your care and ops teams, and stay involved through optimization. One partner from first audit to live retainer.
Beyond isolated bots. We design coordinated systems of AI agents that route, draft, retrieve, escalate, and report — a digital operations layer built around how your health organization actually runs.
No vendor lock-in, built for healthcare data sensitivity from day one. We work around your EHR, practice management, payer, and revenue-cycle systems and the tools your team already lives in. Workflow first. Tool second.
Each module plugs into the same Nona core. Real product, real data.
Turn AI into an operating capability for healthcare.
Our flagship engagement. We map your clinical and operational goals, workflows, systems, data sources, and bottlenecks, then design and implement a coordinated, HIPAA-aware ecosystem of AI agents and automations that runs the work — not just answers questions.
How healthcare AI systems mature.
After launch, AI systems keep evolving — models change, clinical and billing workflows shift, edge cases surface, care and ops teams find new use cases. Our retainers maintain, tune, and expand what we built so the investment compounds instead of decaying.
Practical AI for the healthcare workflow eating your week.
Focused builds for a defined workflow or pain point. Patient intake and triage, prior-authorization prep, referral coordination, claims and denial routing, clinical documentation support, internal knowledge — one or two agents shipped quickly, with the option to expand into a full ecosystem later.
Each module plugs into the same Nona core. Real product, real data — captured live from the IPI deployment.
Turn AI into an operating capability for healthcare.
Our flagship engagement. We map your clinical and operational goals, workflows, systems, data sources, and bottlenecks, then design and implement a coordinated, HIPAA-aware ecosystem of AI agents and automations that runs the work — not just answers questions.
[ How we ship ]
Every engagement follows the same three-month cadence. Strategy, build, launch — then the retainer that compounds value over time.
Workflow audit, AI opportunity map, agentic architecture, and a build plan tied to measurable outcomes. By close of month, you have the roadmap and the build is scoped.
We prototype, integrate, and test with your team. By the end of the month, working agents are running on real data with full audit trails and human review where it matters.
Training, go-live, KPI dashboard, and the optimization backlog. Then the retainer that maintains, tunes, and expands the system as workflows evolve.
EHRs, claims systems, scheduling and patient portals, HL7/FHIR feeds, databases, and custom APIs. We integrate where the work already lives — not where a single AI vendor wants you to migrate.
[ Built to defend ]
Encryption, isolation, uptime, audit — the baseline your security team checks against. Nona ships with these on day one.
Encryption
AES-256 at rest, TLS 1.3 in transit. Keys rotated quarterly. Built for PHI handling.
Data isolation
No shared model fine-tuning on your data. Patient data stays in your tenant.
Access control
HIPAA-aware access patterns. BAAs supported. Every PHI touchpoint is scoped and logged.
Audit
Every agent decision logged with the input, the rule, and the human override — ready for compliance review.
Every engagement starts with a 30 minute working session. We map the workflow, identify your highest-leverage AI opportunity across clinical and operational workflows, and send a tight proposal within two business days.
Still not what you needed? Send us a note and we will reply with specifics within one business day.
We build for healthcare data sensitivity from the start. Workflows that touch protected health information run on private model deployments, on-tenant infrastructure, or strict data-isolation patterns, with role-based access and full audit logging. We support Business Associate Agreements and follow the compliance requirements you bring to discovery. We never make blanket compliance claims before scoping your environment.
We are platform-agnostic. Our agents integrate with major EHR and practice-management systems, payer portals, clearinghouses, and the rest of your stack through APIs, HL7/FHIR, and interface engines like Redox. The architecture follows the systems and data residency requirements you bring to discovery.
A workflow audit. We map the clinical and operational work your teams do every day — intake, prior auth, scheduling, documentation, revenue cycle — identify the repetitive and coordination-heavy tasks, and score the AI opportunities by value, effort, and adoption readiness. You leave with a prioritized roadmap, whether or not you build with us.
We start with workflows where time, throughput, accuracy, or capacity can be measured — turnaround on prior auths, denial rates, hours returned to care teams. Baseline first, then implement, then measure against the baseline. Most engagements show meaningful operational improvement within the 3-month implementation window — but we never promise ROI before discovery.
Sometimes. Most internal teams know the systems and the workflows but lack time, AI implementation experience, or workflow-design capacity — and healthcare adds compliance and integration complexity. We accelerate the work and transfer the methodology so your team builds the next one. The train-the-champion retainer is built around this.
Brittle automation usually fails because the workflow was not mapped clearly, exceptions were not designed for, or clinical and administrative adoption was treated as an afterthought. Our delivery model centers workflow documentation, human-in-the-loop design, training for care and ops teams, and post-launch optimization — the parts most automation projects skip.