Automation that holds up
in a validated environment

Healthcare and life sciences automate under constraints most sectors never meet: clinical accuracy, patient data protection, GxP validation. We design for those from the start, rather than adapting to them once the automation is already built.

The Problem

Where healthcare automation stalls

In this sector the documentation and the traceability are as much the deliverable as the automation. Standard tooling doesn't account for that, which is where the following come from.

01

EHR and claims system fragmentation

Clinical systems, payer portals and revenue cycle platforms don't integrate, so someone bridges every interface by hand. Usually across sites that each configured their EHR differently.

02

Prior authorisation volume

Authorisation requests get assembled from clinical notes against payer-specific criteria, by people. Care is delayed and clinical capacity goes into paperwork.

03

Claims denial and appeals burden

Denials arrive with reason codes that need clinical documentation to contest. High volume, deadline-bound, almost entirely manual.

04

GxP documentation burden

Validation, change control and submission documentation demand extensive evidence, and producing it consumes scientific and quality capacity.

05

Pharmacovigilance case volume

Adverse event narratives arrive as unstructured text in several languages, needing coding and assessment at a volume that grows faster than headcount ever will.

06

Multi-site operational variance

A network of sites runs the same process six different ways, which makes standardised automation fragile and estate-wide governance genuinely hard.

92%

Reduction in documentation time

6,500+

Bots deployed globally

100%

PII safe

INDUSTRY OVERVIEW

Healthcare's documentation problem is an automation problem

Healthcare and life sciences organisations produce enormous volumes of documentation — clinical, regulatory, administrative — and most of it gets assembled by people whose expertise lies somewhere else entirely. Engineering capacity, clinical capacity and quality capacity all go into producing evidence rather than doing the work the evidence describes.

Intelligent automation changes that maths. Leading networks and pharmaceutical organisations are extracting structure from clinical documentation, absorbing denial and authorisation volume inside the automation, and generating validated documentation in minutes, with the PII protection and audit traceability that regulators and patients both expect.

Why AutomationCOE

Why AutomationCOE for Healthcare & Pharma

We connect clinical, payer and quality systems through an automation layer that's governed and validated, not improvised.

ARIA Logo
Stage 1

Discover with ARIA

ARIA discovers your clinical and administrative operations — authorisation workflows, claims processing, documentation assembly — and generates structured blueprints with PII detected and anonymised by default. Process recordings in healthcare contain patient data. ARIA is built on that assumption.

Learn about ARIA
Stage 2

Deliver with 5D1S

The 5D1S methodology delivers inside validated environments, with reusable components spanning EHR, payer and quality systems, and validation evidence produced by the process itself rather than reconstructed for the auditor.

Explore the framework
AURA Logo
Stage 3

Sustain with AURA

AURA monitors your estate in real time, tracking dependencies across clinical systems that change without warning, and predicting failures before they touch a care pathway or a submission deadline.

Learn about AURA

USE CASES

Healthcare & Pharma use cases

Healthcare

Claims denial triage

Denial reasons read, supporting clinical documentation retrieved, appeals assembled. Only genuinely clinical judgement gets escalated.

Healthcare

Prior authorisation

Authorisation packages built from clinical documentation against payer-specific criteria, then submitted and tracked without anyone reassembling them.

Pharma

Regulated document assembly

Submission and validation documentation generated and cross-checked inside GxP environments, with every source and edit attributable.

Pharma

Adverse event processing

Case narratives processed and coded across languages, with confidence thresholds calibrated to the cost of a missed signal.

SERVICES

Relevant solutions for Healthcare & Pharma

SUCCESS STORIES

Proven results in healthcare and life sciences.

Healthcare network, 12 sites

No automation strategy and reactive bot development across 12 sites, an 18% claims denial rate, and no visibility into which automations were contributing to the failures.

ARIA-powered discovery surfaced 280 automation opportunities. The estate was remediated to standard, sequenced into a governed roadmap, and brought under AURA monitoring.

Claims denial rate down to 4.3% within the year.

Read full case study

Top-5 pharma, validated environment

Clinical documentation assembled by hand under GxP constraints, consuming scientific capacity and carrying PII exposure risk at every handoff.

ARIA-generated documentation with PII detection and anonymisation, delivered inside the validated environment with full change control.

Documentation generated in minutes. Time down 92%, GxP aligned, 100% PII safe, 100% audit pass rate.

Read full case study

BUSINESS OUTCOMES

Measurable impact in healthcare and life sciences.

From active enterprise deployments across healthcare networks and pharmaceutical organisations.

92%

Faster documentation

Clinical and regulatory documentation generated in minutes rather than days, giving capacity back to the people who should be doing the science.

76%

Lower claims denial rate

Denial triage and appeal assembly absorbed inside the automation, with clinical judgement escalated rather than the whole case.

100%

PII safe

Patient data detected and anonymised at the point of discovery, not remediated later when someone spots it in a process recording.

100%

Audit pass rate

Documentation, traceability and change control produced by the process, not assembled for the inspection.

INSIGHTS

Related reading

View all insights →

Why Automation Programmes Stall in the First Six Weeks

How Enterprise AI Is Reshaping Business Decision-Making in 2025

FAQ

Common questions about AutomationCOE.

Not finding your answer? Email us directly.

AI and intelligent automation can reduce manual work across healthcare and life sciences processes such as claims processing, prior authorization, clinical documentation, regulatory documentation, and adverse event processing. Automation COE uses ARIA for process discovery and documentation and AURA for runtime monitoring, helping organizations improve operational efficiency while maintaining traceability and governance.
AI automation can assemble prior authorization packages by extracting relevant information from clinical documentation, applying payer-specific criteria, and submitting and tracking authorization requests. AutomationCOE is designed to automate these repetitive workflows while reducing the manual effort required to prepare and manage authorization cases.
Yes. AutomationCOE can automate claims denial triage by reading denial reasons, retrieving supporting clinical documentation, and assembling appeal packages. Cases requiring genuine clinical judgment can then be escalated to the appropriate team, reducing the amount of manual work involved in high-volume denial management.
AutomationCOE supports regulated document assembly within validated GxP environments. ARIA can generate and cross-check submission and validation documentation while maintaining traceability for sources and edits. This helps pharmaceutical organizations reduce documentation effort while supporting validation, change control, and audit requirements.
ARIA is designed with patient-data protection in mind. During process discovery, it detects and anonymizes personally identifiable information (PII) by default, helping healthcare organizations reduce exposure of sensitive patient information in process recordings and automation documentation.
AI automation can process unstructured adverse event narratives across multiple languages, support coding and assessment, and apply confidence thresholds appropriate to the risk of missed signals. This can help pharmaceutical organizations manage growing pharmacovigilance case volumes without relying entirely on manual processing.