Batch records, validation packs and regulated documents still move through page by page review. Benchmark builds AI that reads them, flags what needs a human and keeps the evidence trail intact, so release stays fast and defensible.
Two things changed for life sciences technology teams in the last eighteen months, and both point the same way.
Updated in February 2026 to align with the Quality Management System Regulation, and superseding the relevant section of the 2002 software validation guidance.
The European Commission and the PIC/S inspectors working group consulted on a rewritten Annex 11, a revised Chapter 4 and a new Annex 22 on artificial intelligence. None has been published as final, so none is yet operative.
At the same time, tolerance for a two-year validated release cycle is falling.
The new expectation is about engineering evidence rather than document count.
“Benchmark works at that level.
We build and assure the systems, we automate the testing that keeps them qualified, and we deploy AI where the reviewer keeps the decision.
Batch record review, deviation and CAPA handling, release documentation and shop floor systems. The pressure here is cycle time: a record waiting for a reviewer is inventory that cannot ship.
Artwork, labelling copy, submission content and change control across markets that do not harmonise.
The team carrying the computer software assurance transition and the Annex 11 rewrite.
Serialisation systems built for DSCSA are now permanent infrastructure that has to integrate with everything else.
We build life sciences applications end to end, from architecture through release. Twenty years of product engineering discipline, applied to systems that have to hold up under inspection.
Modernising a qualified system is a sequencing problem before it is a technology problem. We assess the estate, define the target and order the migration so qualification is never broken mid transition. This is also where supplier oversight and access management get designed in rather than retrofitted.
Applied AI for the work that consumes the most review effort: artwork comparison, batch record checking, document extraction. Deployed as accelerators, with the model's role bounded and its output reviewable.
This is what makes risk-based assurance practical rather than theoretical. Assurance still needs objective evidence, and automated regression produces it repeatably. FableRun generates and maintains suites so a qualified system can change without re-testing effort blocking the change.
Controlled, auditable pipelines. Continuous delivery in a GxP environment is now a design problem rather than a prohibited one, and the change controls still have to be evidenced.
Six areas of life sciences where Benchmark has shipped working systems, not slideware.
Where we go deepest, and where the product came from
The reviewer sees the exceptions, not every page
Evidence you can query, not evidence you file
Extract once, reuse across submissions
Automated evidence is what makes assurance work
Compliance infrastructure as a permanent system
Artwork and label review that is manual, repetitive and unforgiving.
Automated comparison of packaging artwork against approved content, flagging text, regulatory and formatting differences so the reviewer works through exceptions rather than every line. Built to leave a record of what was checked and what was found.
Explore LaibelBatch record review that holds up product release.
Automated checking of batch and production records for completeness, missing entries and deviations, so quality review starts from a prioritised exception list rather than page one.
Explore BMR/BPR
Validation evidence that lives in documents nobody can query.
Validation lifecycle management that keeps protocols, traceability and periodic review in one place, so a change impact assessment takes hours rather than weeks.
Explore VruuumXtractly handles the unstructured regulatory and quality documents that feed these processes, and FableRun generates the automated regression evidence that keeps a qualified system changeable.
