Features for everyday research

Our platform combines data collection, process documentation, and quality metrics in one interface. This way, you keep track of ongoing experiments and can trace results reproducibly.

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Centralized data collection

Capture experimental data directly at the workplace – with standardized forms that can be adapted to your measurement series. No duplicate entries, no lost notes.

Uniform structure for all projects

Process documentation

Store standard operating procedures and checklists digitally. Every change is logged, so your team always works according to the latest status.

Audit trail and versioning included

Quality metrics

Track deviations, repeat rates, and processing times via clear dashboards. This allows you to identify early where processes need adjustment.

Metrics directly from project data

Roles and approvals

Define who may view, edit, or approve data. Clear responsibilities increase traceability and relieve the project management.

Individual permission models

Feedback from research practice

What project managers and laboratory supervisors report after switching to our platform.

The introduction of LabGrowth has triggered noticeable changes in many teams: fewer manual transfer errors, clear responsibilities, and documentation that holds up during audits. The following voices show how different the starting points were – and how similar the results.

Process documentation · Quality management

Previously, we kept experimental data in Excel spreadsheets and paper protocols. Switching to the central platform helped us record all steps of an experiment consistently. During the last internal review, we did not have to reconstruct a single data record retrospectively.

Ing. Nicole Brunner B.A. · Head of Analytics
Data analysis · Project metrics

What convinced me is traceability. Each entry is assigned to a person and a timestamp, and changes remain visible. For our team, this means fewer queries and more trust in our own figures.

Ms. Christina Graf · Project Coordination
Workflow standardization · Audit trail

We have multiple sites that worked differently. With the standardized templates and checklists, data capture now runs the same way everywhere. This saves training time and makes results comparable.

Markus Schachner B.A. · Site Research Manager
Quality assurance · Role concepts

The role and approval processes have made our documentation significantly more robust. We can precisely control who may change data and who can only read it. Previously, this was a constant point of discussion.

Natalie Unterberger · Quality Officer
Process optimization · Experiment planning

For me, the biggest gain was the overview. I can see at a glance which experiments are running, which data is missing, and where bottlenecks exist. I now create the monthly project reports in a fraction of the time.

Sophia Maier · Research Associate

Notes and Scope

This page describes the features of the Laboratory Growth Analytics platform for research organizations. All information regarding processes, data management, and quality standards is provided for general informational purposes and does not replace individual consultation. The specific configuration depends on the requirements of your laboratory.

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