Lightening the documentation burden, within a validated framework.
Quality assurance, batch release, regulatory affairs, pharmacovigilance, supply: we automate the collection, compilation and preparation of documents. Decisions remain with authorised personnel.
What is at stake for leadership.
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Compliance and data integrity
GMP-compliant processes, with data that is attributable, traceable and verifiable.
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Batch release lead time
Reduce the time between end of manufacturing and release, without lowering the level of control.
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The documentation burden
Procedures, deviations, CAPA, product quality reviews, regulatory dossiers: a volume that ties up expert profiles.
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Continuity of supply
Anticipate shortages and share a single view across supply, production and commercial teams.
The time-consuming tasks, and what we put in place.
Quality assurance
Ensures compliance of the quality system.
- Write and investigate deviations and CAPA
- Manage change control
- Compile data for the annual product quality review
- AI agentData compilation and first drafts of reports, reviewed and approved according to your procedures.
- EcosystemIntegration with the existing quality management system (QMS).
- SteeringQuality indicators: closure times, recurrences, trends.
Qualified Person and batch release
Certifies and releases batches.
- Review batch records in full
- Search for discrepancies and their justification
- Gather quality control results
- SteeringReview by exception: automated batch record checks, only discrepancies are escalated.
- AI agentPre-qualification of discrepancies; the release decision stays with the Qualified Person.
Regulatory affairs
Obtains and maintains marketing authorisations.
- Prepare and update marketing authorisation dossiers in CTD format
- Handle variations
- Carry out regulatory intelligence
- AI agentStructured regulatory intelligence and preparation of dossier sections from source data.
- InterfaceTracking of regulatory commitments and deadlines.
Pharmacovigilance
Monitors medicine safety.
- Triage and enter reported cases (ICSRs)
- Review the scientific literature
- Prepare periodic safety reports
- AI agentCase triage and pre-entry, literature pre-screening, with systematic human review.
Supply chain
Ensures product availability.
- Consolidate forecasts and capacity for S&OP
- Track shortage risks
- Coordinate production and distribution
- SteeringS&OP data consolidated automatically, shortage alerts.
- EcosystemERP, production and distribution integration.
Batch record review.
- Batch record compiled Manual
- Page-by-page review Manual
- Search for discrepancies Manual
- Deviations written up Manual
- Batch release Human decision
- Batch data collected Automated
- Automated checks, review by exception Automated
- Discrepancies flagged and pre-qualified AI agent
- Review of discrepancies only Human decision
- Release by the Qualified Person Human decision
- Manual
- Automated or AI agent
- Human decision
What the task costs, what the solution costs.
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What the task costs today
Time spent × frequency × full cost of the roles involved, plus the cost of errors (credit notes, disputes, re-keying) and of delays.
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What the solution costs
A scoped diagnostic, then a staged build, each stage priced before it starts. Running costs (hosting, licences, maintenance) are stated from the outset.
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The return
Calculated task by task, on your volumes: hours redeployed, errors avoided, lead times shortened. We start with the tasks that pay back fastest.
We do not publish an average gain: it depends on your processes and volumes. The diagnostic quantifies it, task by task, before any commitment.
What we are asked.
- Which pharma roles can be automated with AI?
- The documentation tasks of quality assurance, batch release (review by exception), regulatory affairs (regulatory intelligence, dossier preparation), pharmacovigilance (case triage and pre-entry) and supply chain (S&OP consolidation), within a validated framework.
- How do you automate batch record review?
- Through review by exception: batch data is collected and checked automatically against rules defined with quality assurance; only discrepancies are presented to the Qualified Person, who decides.
- Can AI be used in a GMP environment?
- Yes, provided its scope is defined, the system is validated using a risk-based approach, every action is traced and the decision is left to an authorised person. We design alongside your quality assurance team from the outset.
- How do you speed up writing CAPA and product quality reviews?
- An agent compiles data from the source systems and prepares a structured first draft; quality experts review, complete and approve it according to your procedures.
- Can AI replace part of quality assurance work?
- The compilation and preparation part, yes: data collection, batch record checks, first drafts of deviations, CAPA and product quality reviews. Decisions, approval and batch release remain with authorised personnel: that is a regulatory requirement.
An architecture that fits what you already have.
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Computerised system validation
Risk-based approach, with validation documentation supplied with every delivery.
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Data integrity
Audit trail, access control, electronic signatures: compliance with current requirements.
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Integration, not replacement
QMS, LIMS, ERP, MES: we start from your existing systems and connect them.
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Governed AI agents
Defined scope, systematic human review, a log of every action.
Describe what’s holding your teams back.
A first conversation to qualify your need. Then a scoped diagnostic: the scope, the solution, the estimate.
Discuss your projectReply within 48 business hours.