Marquee differentiator

Adopt AI inside regulated workflows — responsibly.

Anova leads governed AI adoption for healthcare and regulated teams: clear PHI boundaries, provenance and auditability, and human-in-the-loop review so AI improves outcomes without compromising trust or compliance.

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Best fit

Healthcare and regulated software teams putting AI into real workflows that touch sensitive data and decisions.

Problem

What usually needs to change

AI is promising, but moving it into a regulated workflow raises questions about data boundaries, provenance, accountability, and human oversight that a demo never answers.

Outcome

What Anova builds toward

AI capabilities that ship with defensible data boundaries, traceable provenance, human review where it matters, and governance that holds up under scrutiny.

What the engagement covers

AI use-case feasibility and risk assessment

PHI and sensitive-data boundary design

Provenance, auditability, and traceability

Human-in-the-loop review and accountability workflows

AI governance policy and rollout leadership

Marketing contact
Working hours

Mon-Fri: 9 am — 6 pm

Located at

Marlton, NJ, 08053

Book a fit review

Book a fit review directly

30 minutes. You'll leave with a clear read on your top architecture and compliance risks — whether or not we end up working together.

Best fit for founder-led healthcare and regulated software teams entering the phase where architecture, compliance, interoperability, and AI governance start to matter more than raw build speed. Probably not a fit if you are looking for build capacity or hours.

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Share the engagement type, the outcome you want, and your technical context so Anova can confirm fit and the clearest next step.

30 minutes. You'll leave with a clear read on your top architecture and compliance risks — whether or not we end up working together. Share enough context to confirm fit, conflicts, and whether the right next step is a 2-week fixed-fee sprint: Architecture & Sequencing Sprint.

Examples: EMR/EHR, CRM, scheduling, intake, RCM, data warehouse, cloud platform, AI tooling, internal services. Please do not include PHI or patient details.
This helps separate urgent revenue, operations, or customer-experience problems from nice-to-have work.

Areas of focus

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