About DataChaperone
Why we exist
CROs, CDMOs and specialized labs produce the data that drive critical decisions for life science innovation. Yet, the crucial step of transforming raw data into decision-ready results still relies heavily on fragmented workflows and subjective judgement.
That reliance comes at a cost. A 1% manual error rate is significant at scale, warranting multiple layers of checks and reviews. In practice, repetitive analyses and reporting can consume up to 25% of scientists’ time. Time that can be spent better.
DataChaperone was founded in 2023 to address this systemic inefficiency by making data analysis and reporting fast, objective, traceable, and reproducible. We enable analytics to scale so organizations can grow efficiently—or operate more effectively with fewer resources.
What we do
DataChaperone captures analysis logic and turns it into governed workflows. Raw assay files go in, relevant metadata is pulled from your LIMS, agreed calculations and QC rules are applied, and review-ready results are produced in your desired format or pushed to the ELN. Fully aligned with your existing process and therefore easy to integrate.
We don’t deliver standalone tools and walk away. We work closely with you to design and evolve solutions that fit your workflows as they grow and change. This approach allows you to scale data analysis with confidence. Together we improve efficiency and consistency without disrupting what already works for you.
How we work
Our approach is pragmatic: start small, prove value quickly, and then scale.
We typically begin with a Workflow Scan. Together with your team, we map how an analysis workflow runs today. An analysis workflow includes not only the core analysis, but also the upstream inputs and downstream steps leading to decision-ready results.
Based on this understanding, we implement Workflow Automation: a governed, production-ready version of the workflow that fits your SOPs and laboratory reality. Raw data flows in, analysis logic and quality controls are applied consistently, and results move downstream in a structured, traceable way.
We deliver the first production-ready workflow within 4–6 weeks. From there, we continue as a long-term partner. Teams typically expand from a single workflow to multiple assays, introduce Workflow AI where expert interpretation is required, and implement meta-analyses once results are available in a standardized form.
You set the pace; we ensure each step remains aligned with your processes, regulatory context, and business objectives.
Turning lab data into decisions
We help CROs, CDMOs and specialized labs turn raw assay data into consistent, audit-ready results and reports.
Instead of replacing your platforms or processes, we automate one critical workflow first. Following the Workflow Scan, we jointly define a project to implement Workflow Automation. Once we start building, you’ll have a working, production-ready solution in 4–6 weeks.
From there, we become your long-term partner: maintaining and evolving your workflows, integrating with existing systems, introducing Workflow AI, and enabling DataChaperone Meta-Analysis as you scale.
DataChaperone:
✓ Automates data import, transformation and quality control.
✓ Generates audit-ready reports with full data lineage.
✓ Deploys custom solutions with off-the shelve speed.
✓ Integrates with existing LIMS, ELN, and instrumentation.
✓ Provides meta-analysis capabilities across multiple studies.
✓ Offers custom automation to fit unique lab workflows.
DataChaperone is the objective, traceable analysis layer for modern labs.
Lars-Eric leads DataChaperone with a clear view on the lab of the future. From his experience leading teams at a CRO scale-up, he understands why manual, fragmented workflows limit scalability and introduce subjectivity.
In his view, the lab of the future is defined by software that turns analytics from a bottleneck into a competitive edge and driver of innovation.
That vision led to DataChaperone: an integrated analysis layer that turns data analysis and reporting into a scalable, auditable process.
Meet your new data analyst. It’s software.
Lars-Eric Fielmich – CEO
Following his personal goal to accelerate life-science innovation, Bas leads DataChaperones efforts to build a reliable, scalable and explainable data-analysis platform that teams can validate, trust, and use with confidence.
He has a background in physics and data science, holds a PhD from Utrecht University and has 10+ years of experience deploying AI models in production environments.
Bas Cloin – CTO
Start with one workflow
You don’t need a full transformation to get started.
Most teams begin with a single, high-impact workflow.
We scan it, automate it, and deliver a working result in weeks.
From there, you decide how far to scale.
Why teams start this way:
✓ See impact quickly
✓ Get buy-in across teams
✓ Validate the approach with minimal risk
✓ Free up time for higher-value work