# AI agents for healthcare and life sciences.

> Agents and data platforms for providers, labs and life sciences companies, built into the clinical, quality and scheduling systems already in place.

Scheduling, documents and quality records, with clinicians in control.

Agents and data platforms for providers, labs and life sciences companies, built into the clinical, quality and scheduling systems already in place, with people approving what matters.

- 01 Admin takes clinical time Scheduling, forms and follow-ups take hours that clinicians and lab teams would rather spend on care and science.

- 02 Quality records pile up Every batch, trial and inspection produces documents that must be complete, checked and traceable.

- 03 Rules change by market Labels, claims and procedures must match the rules of each country before anything ships.

## Agents across care and research.

The agents Twistag builds most often for healthcare and life sciences, from scheduling to compliance. Each one keeps a qualified person on the decisions that matter.

### 01 · Schedule

#### Appointment coordination agent

Books, moves and confirms appointments across calendars and sends preparation instructions.

### 02 · Staff

#### Staffing planner

Forecasts demand by site and day and builds rotas that move people between locations before agencies are booked.

### 03 · Document

#### Document intake agent

Reads forms, emails and scans, extracts the fields that matter and files them in the right system.

### 04 · Quality

#### Quality report agent

Pulls inspection data into batch reports, spots drift early and links each finding to the procedure behind it.

### 05 · Comply

#### Regulatory check agent

Checks products, labels or communications against the rules of each market, citing the regulation behind each finding.

#### Policy question agent

Answers staff questions on internal policy and regulation from approved sources only.

### 06 · Answer

#### Reply drafting agent

Classifies each message, pulls up the account and drafts a reply in the house voice, checked against written guidelines.

## Healthcare work.

## Three steps from question to daily use.

- 01 Find where it pays back 2–4 weeks · from €5,000 Map the operation from scheduling to compliance, score each process on value, effort and risk, and leave with a shortlist and a 90-day plan.AI Readiness Sprint→

- 02 Build the first agent 6–12 weeks One agent on real data, connected to the scheduling, document, quality or ERP systems already in place, with people approving each action.Multi-agent Systems & Agent Engineering→

- 03 Scale and govern Ongoing More agents on one platform, each with its own access rights, EU AI Act risk class and audit log.Agent Governance & Security→

## About AI in healthcare.

Which processes should get an agent first?

Which systems do the agents connect to?

How long until the first agent runs every day?

How is health data protected?

How does the EU AI Act apply in healthcare?

Who owns what is built?

## Let’s talk.

Tell us about the company and what it needs. A senior lead takes it from there.

A senior lead replies within one working day.

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Source: https://twistag.com/industries/healthcare-life-sciences