RPA + AI + agents where it actually earns its keep.
Process discovery, automation architecture, agentic orchestration and lifecycle management — for regulated back-office and lab workflows.
Intelligent automation combines rules-based process automation with AI for the judgement-adjacent steps. In regulated work the division matters: anything that must be reproducible and explainable should be computed deterministically, and the AI confined to drafting, extraction and retrieval where a human reviews the output before it becomes a record.
Outcomes you can expect
- Automation opportunity map
- Delivered automations
- Lifecycle management
Intelligent Automation is delivered by our ai transformation practice. Where it saves time, the team uses our products: GxP Copilot for validation lifecycle work and TraceDraft for clinical documentation.
Explore related capabilities: AI Strategy, AI Governance, AI Validation, GenAI Adoption.
RPA in Regulated Environments: Validation is Not Optional
Robotic Process Automation tools — UiPath, Automation Anywhere, Power Automate — that operate in GxP-regulated processes are computerised systems subject to the same validation requirements as any other GxP software. An RPA bot that processes ICSRs, updates a validated LIMS, or generates a GxP-regulated document is performing a GxP-critical function. If that bot's operation is not validated, the outputs it produces are not from a validated system — regardless of whether the downstream system is validated.
RPA validation follows GAMP Category 5 logic for bespoke bots that perform regulated functions: the bot's specification, design, test, and deployment must all produce validation documentation. The most common mistake in regulated RPA deployment is to validate the RPA platform (Category 4, leveraging the vendor's documentation) without validating the specific bot (Category 5, requiring full lifecycle documentation). Our intelligent automation practice delivers end-to-end validated RPA for regulated processes — from process specification through bot deployment with IQ/OQ evidence — so that the automation produces outputs that can be used in GxP decisions.
Identifying the Right Processes for Automation
Not every manual process in a life sciences organisation is a good automation candidate. The processes that deliver the highest return from intelligent automation are those that are: high-volume (the time saving per transaction justifies the automation investment); rule-based (the process can be described with sufficient precision that a bot can execute it without ambiguous judgment calls); stable (the process does not change frequently enough to make bot maintenance cost-prohibitive); and digital (the inputs and outputs are in electronic form without requiring paper document handling or physical access).
Process discovery for intelligent automation candidates in life sciences organisations typically surfaces the same categories of high-ROI opportunities: regulatory submission compilation and cross-referencing; LIMS data transfer between systems that lack native integration; safety case intake and narrative first-draft generation; periodic review notification and tracking; and label text extraction and comparison. Our process discovery methodology applies a scoring framework that ranks automation candidates by ROI, implementation complexity, regulatory risk, and maintenance burden — producing an automation roadmap with a realistic sequencing based on organisational readiness.
See it on your own system.
Bring a URS or a system. We show you the validation package it produces.
- We reply within one business day
- We run your URS live on the call
- You get a clear plan and scope