02Industry

Healthcare & Life Sciences

Turning patient data into better care — without ever forgetting the human at the centre.

01Position

Where we stand.

Healthcare's data problem isn't a shortage — it's fragmentation. Patient records, claims, devices and trials live in adjacent rooms that rarely speak the same dialect.

We work with providers, payers and life sciences teams to translate fragmented signals into safer, faster, more humane decisions — with the governance and audit trail the regulator expects.

02Challenges

Three persistent pain points.

01

Fragmented patient records

Care continuity suffers when systems can't agree on identity and history.

02

Manual prior-auth and intake

Hours of clinician time disappear into forms and faxes.

03

Model risk and bias

Clinical AI must be defensible — to the patient, the regulator, and the board.

(03)Approach

How we work the brief.

We pair clinicians and engineers from day one. Workflows are observed before they're optimised, and every model ships with an evaluation harness and a refusal mode.

From AI scribes to anomaly detection on patient cohorts, from claims automation to safety surveillance — Zenanlity builds healthcare AI you can defend in a deposition.