An execution layer for objective, traceable analysis
DataChaperone is a managed execution layer for life science data analysis workflows. It sits between instruments, ELN/LIMS and reporting systems, ensuring analyses run in a consistent, objective and traceable way.
Workflows are executed as explicit, versioned processes with full lineage from raw data to reported result.
Deterministic workflow execution
At the core of DataChaperone is deterministic execution. Once a workflow is defined, it always runs the same way. The same inputs produce the same outputs, independent of who runs it.
Each run records inputs, parameters, code/model versions, QC outcomes and approvals. This creates an audit trail without manual reconstruction.
AI where it adds objectivity
Some analysis steps require interpretation, such as pattern recognition, peak detection or image-based classification. DataChaperone supports these cases using deterministic AI methods (for example ML or CNNs) that produce the same output for the same input.
In regulated environments, generative AI such as an LLM is not used in the execution path. It may be used outside execution, for example to generate a report that scientists review and approve.
Validation and data integrity by design
Workflows and models move through development, staging and production environments. Validation happens before promotion, using known datasets.
Because execution is deterministic and manual steps are reduced, validation shifts from deciphering files to reviewing defined workflows. This shortens review cycles and supports data integrity principles such as ALCOA++ by design.
Each run records inputs, parameters, code/model versions, QC outcomes and approvals. This creates an audit trail without manual reconstruction.
Integration and security
DataChaperone integrates with existing ELN and LIMS systems, which remain the systems of record. Relevant metadata is pulled from these systems, and structured outputs are pushed back.
The platform is cloud-native, hosted on Microsoft Azure, with customer data stored in North and West Europe. Data is encrypted in transit and at rest, integrity checks are applied, and access is controlled via SSO and role-based permissions.
What our users say
“We can turn prototype analyses into workflows that scale beyond the original developer without the burden of deployment and maintenance.”
– CRO, Senior Data Scientist