WHPLAgentic Intelligence for Regulated Life Sciences
Regulatory & Quality Intelligence

Intelligence for regulatory and quality workflows where evidence must stand up to scrutiny.

Connect fragmented evidence, documents and decisions across regulated workflows—so teams can review faster, understand change, maintain traceability and act with greater confidence.

Regulatory & Quality Intelligence from WHPL applies Life Sciences-specific software and intelligence capabilities to evidence-intensive regulatory and quality problems.

Discuss Your Regulatory or Quality Challenge →
CONNECTED REGULATORY EVIDENCEEvidence in context. Decisions under control.
REGULATORYSubmissionsSource documents
QUALITYCAPA & deviationsInspection evidence
STRUCTURED EVIDENCE RELATIONSHIPSConnected Evidence
Source lineageChange impactDecision contextReview state
Review fasterFind relevant evidence
Understand changeSee affected outputs
Maintain traceabilityKeep the evidence path visible
HUMAN ACCOUNTABILITYQualified professionals interpret, decide and approve.
From documents to connected evidence

Connect the evidence first. Then create, review and control the outputs.

WHPL is developing regulatory and quality intelligence around a simple principle: evidence relationships and workflow context should exist before intelligence is asked to support a regulated output.

FRAGMENTED INPUTSSource evidenceDocumentsDecisionsReview history
WHPL APPROACHConnected EvidenceStructured relationships · traceability · controlled workflow
PROFESSIONAL OUTCOMEClearer regulated decisionsBetter evidence · stronger traceability · clearer context
The objective is not autonomous decision-making.

It is to give qualified professionals better evidence, stronger traceability and clearer context for regulated decisions.

Where intelligence can create value

Five evidence-intensive workflows where connected context matters.

The starting point is the operational and evidence burden—not a generic AI deployment.

01

Regulatory Evidence Reconciliation

Bring related sources, conclusions and review context together so inconsistencies can be identified and resolved with an inspectable evidence path.

02

Submission Readiness & Source Traceability

Make supporting sources, open review items and evidence lineage easier to verify before a controlled submission milestone.

03

Change Impact Intelligence

Understand which documents, claims, risks, conclusions and workflows may require review when relevant evidence changes.

04

CAPA & Deviation Evidence

Connect event context, supporting records, actions, review status and decision evidence without obscuring accountable quality judgment.

05

Inspection & Quality Readiness

Improve visibility into evidence completeness, ownership and unresolved questions before inspection or quality-review pressure peaks.

Intelligence that supports human accountability

Technology strengthens the evidence path. Professionals retain the decision.

WHPL applies intelligence within bounded, reviewable workflows so evidence and responsibility remain visible.

01

Evidence-grounded

Relevant outputs remain connected to the source material and relationships used to support them.

02

Traceable change

Teams can inspect what changed, which downstream items may be affected and what remains to be reviewed.

03

Controlled workflow

Review state, ownership, permissions and required handoffs stay visible throughout the process.

04

Accountable approval

Qualified regulatory, quality and Life Sciences professionals remain responsible for interpretation, judgment and approval.

Built for Life Sciences

Domain specialisation. Evidence grounding. Traceability. Workflow control. Human accountability.

WHPL is a specialist Life Sciences technology company. We use AI where it improves a regulated workflow—not as a substitute for Life Sciences expertise or accountable professional judgment.

Domain specialisationEvidence groundingTraceabilityWorkflow controlHuman accountability
Start with the workflow

Have an evidence-intensive regulatory or quality workflow worth improving?

We can start by understanding the current workflow, evidence landscape, review burden and business impact before discussing technology.