Frequently Asked Questions

We remove manual analysis bottlenecks and make your results objective, traceable, and reusable.

In many labs, experiments are digitally documented, but analysis and interpretation still rely on Excel files, scripts, and manual checks. This slows execution, introduces variability, complicates audits, and prevents organizations from extracting insights from their own data.

DataChaperone automates the full analysis process and stores outputs in a standardized format. Execution becomes faster and more consistent, review loops shrink, and results are no longer scattered across files. Structured storage enables meta-analysis and performance insights.

We automate the analysis layer between raw data and your existing systems.

ELNs and LIMS manage experiments, samples, and documentation. DataChaperone automates what happens after data is generated.

Raw data flows from instruments, ELN, or LIMS into DataChaperone. Analysis, interpretation, and reporting are executed automatically within a governed workflow. Standardized results and reports are then written back into your ELN, LIMS, or data platform.

This closes the loop between data capture and decision-making without replacing your infrastructure.

If expert logic can be defined, it can be automated.

Any workflow that follows defined expert logic, whether rule-based or AI-driven, can be translated into a governed workflow.

Examples include:
– Plate-based assays (ELISA, qPCR, xCELLigence, drug screening, …)
– Calibration curve optimization
– QC trending, assay performance and other meta-analyses
– Image classification using convolutional neural networks (AI)
– Flow cytometry, automated gaing with machine learning (AI)
– Chromatography, peak detection and signal-to-noise analysis using machine learning (AI)
– Audit trail review using machine learning (AI)
– Report or protocol generation, including ICH guidelines, using large language models (AI)

If decision-making criteria can be described, we can formalize and operationalize them.

Yes, with flexibility and governance.

Many laboratories rely on complex and linked Excel files where parameters or acceptance criteria differ per project. While flexible, this approach sacrifices control and traceability.

DataChaperone allows project-specific parameters while maintaining version control, auditability, and structured governance. You retain flexibility, but within a production-ready environment.

We use AI where it adds value, always in a transparent and validated way.

We apply deterministic logic (machine learning or convolutional neural networks) to standardize expert interpretation. Generative AI (large language models) is applied to generate reports, ready for review. Models can be trained on your historical data, integrated from your internal team, or based on open-source frameworks of your choice.

We support maintenance and retraining where needed. All models are validated together with your team before deployment, and decisions remains traceable.

Yes, every step is logged and reviewable.

Every input, transformation, parameter, and model decision is recorded in an immutable audit trail. Electronic signatures can be applied where required.

Once a workflow is validated and governed, manual review steps often become structurally unnecessary, which is typically where major efficiency gains are realized.

Yes, security and data sovereignty are built in.

Data is encrypted in transit and at rest, and access is controlled through strict role-based permissions. The platform has successfully passed an independent penetration test as proof of its security.

Data is hosted in secure data centers in North-West Europe. As a European company, we operate under European data protection standards.

You remain fully in control of your data.

We do not access or inspect your scientific data unless explicitly agreed for support purposes. Raw data should remain on your own infrastructure under your control.

You decide whether and how long processed results are stored within DataChaperone. If you discontinue the collaboration, you retain all your data and results. We do not lock you into proprietary data structures.

Your data remains yours.

A platform fee plus workflow implementation.

Pricing consists of a yearly platform access fee combined with implementation of workflows. Workflow implementation is scoped together and executed collaboratively. A percentage of the implementation fee is added to the platform fee to guarantee continued support.

Because each organization’s processes differ, pricing reflects the complexity and number of workflows being automated.

Automation delivers the highest impact in high-throughput, regulated environments.

CROs and CDMOs operate under clear quality requirements and high operational pressure. Small inconsistencies can scale into significant cost or delay.

Automating analysis and interpretation reduces review time, increases reproducibility, accelerates turnaround, strengthens audit readiness, and creates structured operational insights.

Because we combine scientific understanding with workflow governance expertise.

Your expertise lies in science and service delivery. Ours lies in translating scientific logic into governed, automated, and scalable workflows.

We do not simply provide software. We work with you to formalize expert decision-making, remove manual bottlenecks, and build a sustainable digital backbone for analysis and interpretation.

A lab where analysis, interpretation, and reporting are fully digital, governed, and insight-driven.

In the digital lab of the future, data capture, analysis, interpretation, and reporting form a seamless, traceable workflow. Manual Excel processing and fragmented review loops disappear. Decisions are reproducible, auditable, and continuously improvable.

DataChaperone focuses on the analysis and interpretation layer within this ecosystem, enabling laboratories to move from manual execution to structured intelligence.