Limebit
Berlin, Germany
About
Limebit is a Berlin data science and machine learning firm working on real-world evidence, health-insurance routine data and causal methods for pharma and healthcare clients.
Who They Work With
Pharmaceutical companies and statutory health insurers that need analysis to survive a regulatory review and the code to come with it.
Based on 2 client engagements with a source URL · researched 27 Sept 2026
Our Take
A health data science firm rather than a general AI shop, and the reference page reads like a research group's: client, data source, objective, method and focus on every entry.
The strongest is the synthetic-data work for AstraZeneca and Amgen across 2023 and 2024, training deep networks on a German health insurer's data to produce a synthetic set with the same statistical properties and then evaluating fidelity against privacy. Alongside it, machine-learning validation of electronic prescriptions has run in a Kubernetes environment for German health insurers from 2022 to 2025, and a breast-cancer registry analysis for an international pharmaceutical company looks for early indicators of metastasis.
Three commitments are published and they are the reason to take the firm seriously: every figure reproducible from a versioned pipeline rather than a notebook, consultants who read study protocols and statistical analysis plans as a matter of course, and full transfer of code, models and documentation at the end with no license attached.
The weaker fit is a buyer outside health and life sciences, or one who needs an outcome figure before signing, because the references publish method rather than result.
Key strengths
- Full transfer of code, models, documentation and training artifacts at project end, stated as a principle rather than negotiated—no vendor lock-in
- Every deliverable reproducible from a versioned pipeline, published as a commitment against one-off notebooks
- Regulated-domain fluency is specific: real-world evidence, causal inference, Bayesian workflows and cohort phenotyping on statutory health-insurance and registry data
Good to know
- The references publish method and objective but no result—ask what the retaxation and prescription models detect and at what rate
- Bayer, Roche, DAK and the other names carry no described engagement; the written-up work is AstraZeneca, Amgen and anonymized insurers
- A team of two to nine in a domain where projects run for years—ask who covers the engagement if a key person leaves
Reviewed by Gabor Kiss
Founder & Curator, AIAgencies.eu · 9 Sept 2026
Based on the agency's publicly available portfolio. Own this agency? Claim your profile to provide additional context or request a review update.
Notable Clients
Documented engagements: AstraZeneca, Amgen, Bayer, and Roche. 2 of 4 carry a source URL on file.
Also worked with
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