Help & FAQ

Yes. Most customers start with the Operational Hub and add the Management Hub as they scale.

No. q_alizer sits on top of your existing LIMS and ERP. It connects your systems and adds the planning and release layer that's typically missing.

No. q_alizer prepares decisions but does not make them. Release authority stays fully with the QP. The system shows which batches are ready for decision and what information is still missing.

Yes. q_alizer is delivered with a full validation package (IQ/OQ/PQ documentation) and supports 21 CFR Part 11 / Annex 11 requirements.

A typical implementation takes 8–12 weeks. For smaller teams starting with a single hub, we've gone live in as little as 4 weeks.

Not necessarily. For basic setups, our team handles the configuration. For deep LIMS integrations, your IT team will be involved for 1–2 weeks.

Visit our Pricing page for Starter, Growth, and Enterprise options, and see what's included at each level.

We don't offer a self-serve trial, but we do offer a structured proof-of-concept for qualified prospects.

All plans are annual. Multi-year contracts are available with additional discounts.

Yes. We offer volume discounts as well as an Enterprise offering for larger deployments. Get in touch and we will work out a package that fits your scope.

Batch release management is the set of activities and decisions required to confirm a manufactured batch meets quality standards and is ready for release. It spans QC testing, QA review, and the coordination between the two, and directly determines how quickly a batch reaches the market.

Common causes include unclear task priorities, hidden bottlenecks in QC or QA, deviations discovered late, and fragmented visibility across LIMS, QMS, and ERP systems. Most delays come from coordination gaps, not from the actual testing work itself.

Cycle time drops when work in progress is controlled, priorities are visible in real time, and bottlenecks are detected before they block release. This usually matters more than adding headcount or speeding up individual tasks.

Batch release software connects the systems and teams involved in QC and QA into one real-time view, so release readiness, blocking items, and delays are visible as they happen instead of being discovered afterward.

It works by tracking every release relevant activity across QC, QA, and Operations, and by connecting them into a shared, real-time picture, so decisions about release readiness are based on the actual current state, not periodic reports.

QC teams improve performance by replacing static planning with real-time, WIP driven scheduling, so bottlenecks and overload become visible immediately instead of at the end of the week.

QA gains real-time visibility through an independent view into QC and Operations status, without adding transactional workload or waiting for manual status updates and reports.

Excel based planning works for small volumes but breaks down as complexity grows, since it has no real-time updates, no shared visibility, and no automatic bottleneck detection. Batch release software replaces static spreadsheets with a live, shared view.

Power BI is a reporting tool that shows what already happened. Batch release software is an operational tool that shows what is happening right now and helps teams act on it before release is delayed.

A LIMS manages laboratory samples, tests, and results. Batch release software sits on top of the LIMS and other systems to orchestrate the workflow and decisions around release, without replacing the LIMS itself.

QC workflow management is the coordination of testing, review, and approval steps within the quality control laboratory, from sample registration to result approval, so work moves predictably instead of being managed ad hoc.

Turnaround time drops most reliably by controlling work in progress and reducing multitasking, since queueing effects, not raw testing speed, are usually the biggest driver of long turnaround times.

Workload is prioritized effectively when analysts and planners can see real-time status, deadlines, and dependencies across all open work, instead of relying on informal requests or static task lists.

Common measures include throughput, lead time, work in progress, and planning stability. Together they show not just how much work is completed, but how predictably it moves through the lab.

The most useful KPIs are typically throughput, lead time, work in progress, and planning stability, since they explain why performance changes rather than only reporting outcomes after the fact.

Bottlenecks are detected earliest when work in progress and queue times are visible in real time, rather than being identified only once a batch is already delayed.

Excessive work in progress increases waiting time, reduces focus, and destabilizes flow. Controlling WIP is one of the most effective ways to keep lead times short and predictable.

Digital QA operations management gives Quality Assurance a real-time, independent view into QC and operational status, so compliance monitoring and oversight can happen continuously instead of only after the fact.

Deviation management improves when deviations are captured within the same flow as daily execution rather than tracked separately, so they are visible and actionable as soon as they occur.

QA and QC collaborate more effectively when both work from the same real-time data, rather than QA relying on periodic reports or manual updates from QC.

Quality operations improve most reliably by connecting QC, QA, and Operations into one synchronized flow, so decisions are based on current data instead of retrospective reporting.

It connects to the LIMS to read relevant sample, test, and result data, using that information to orchestrate workflow and visibility, without replacing or altering the validated LIMS itself.

It connects to the QMS to include deviations, CAPAs, and change controls in the same real-time flow as QC and release activities, so quality events are visible alongside operational status.

A LIMS manages samples, tests, and results. A QMS manages quality events such as deviations and CAPAs. Batch release management software connects both, along with ERP and MES data, into one real-time view for release decisions.

Each system manages its own function, LIMS for testing, MES for manufacturing execution, ERP for materials and resources, QMS for quality events. Batch release software connects the relevant data from all four into a shared, real-time picture without replacing any of them.

GxP compliant batch release software is built to support regulated pharmaceutical and biotech environments, working alongside already validated systems rather than requiring changes to them. q_alizer is built to be compliant with these requirements, it is not itself a certified system.

Software can support 21 CFR Part 11 requirements such as audit trails and electronic records by working transparently on top of already validated systems. q_alizer is designed with these requirements in mind, without holding a separate certification.

Annex 11 sets EU requirements for computerized systems used in GMP regulated activities, covering areas such as validation, data integrity, and audit trails. q_alizer is built to be compliant with these principles, it is not a certifying body and does not certify systems itself.

Digital workflows improve data integrity by reducing manual data transfer and providing a consistent, auditable record of activity across systems, instead of relying on spreadsheets or disconnected status updates.