A Decade of AI Innovation for Life Sciences
We've been building and deploying proprietary AI models to streamline life sciences workflows for more than 10 years, helping life sciences teams reliably get their products to market and keep them there.
Our AI Technology Stack
More than 25 large language, machine learning, and natural language processing models work together to deliver streamlined, fit-for-purpose workflows.
Large Language models deliver intelligent insights, answer complex questions and create comprehensive summaries
Machine Learning models identify and extract content, enabling precise comparisons
Natural Language Processing models deliver smart recommendations and accurate language translations
Superior Precision & Recall, F1 Scores
Our models are applied to a robust proprietary ontology and consistently exceed industry precision benchmarks. This delivers more accurate results for labeling and regulatory intelligence workflows.
Zero IP Leakage
Our proprietary generative AI/large language models operate in a completely closed ecosystem. Your data, prompts, and insights never leave our secure platform or touch the open internet. We never store or use your prompts.
Accelerated Time-to-Market
Gain dramatic efficiencies by letting our AI streamline your workflows and automate routine tasks, reducing review cycles and eliminating manual data gathering.
360° Market Visibility
Strategize with full and contemporary visibility into the regulatory landscape. Automated notifications keep you informed as market insights change, delivering the right evidence at the right time.
Break Down Silos
Leverage shared insights across your organization, increasing collaboration between regulatory affairs, PV/safety, clinical development medical affairs, and commercial teams.
Life Sciences Expertise
Drawing on more than 20 years of industry knowledge and experience, our models understand regulatory nuance, clinical context, and therapeutic area specificity.
"We believe very much in human-in-the-loop, with individuals at key parts along the process reviewing the outputs the AI is generating, ensuring it's clinically accurate, then ensuring the responses we're generating for clients are as robust as possible."
Rose Higgins
CEO, Dr.Evidence
Curated search strings refined by regulatory experts
Clinical validation at critical decision points
Automated testing combined with subject matter expert review
Continuous model improvement informed by expert feedback
Centralized documentation of all AI requirements
Uncompromising Security & Privacy
Our commitment to security, privacy, and quality is embedded in every aspect of our AI development and deployment.
Closed Ecosystem
All AI models secured within our private platform—never exposed to external services.
No Third-Party LLMs
No use of OpenAI, Microsoft CoPilot, Google Gemini, or external language models.
Zero Data Sharing
Your data, search histories, prompts, and results never leave our platform.
Private Cloud Only
No off-cloud SaaS services, including indexing or vector data stores.
Public Data Training
Models trained only on public or licensed content—never on client data.
Translation
Third party translation model used only for publicly available label translation to English.
Dr.Evidence AI Principles
Our commitment to security, privacy, and quality is embedded in every aspect of our AI development and deployment.
Data Isolation
No client data, search histories, prompts, or results are ever shared outside of the Dr.Evidence platform.
Infrastructure Control
No use of off-cloud SaaS services including indexing and vector data stores.
Model Independence
No reliance on third-party LLMs or embedding models residing outside our private cloud.
Ethical Training
AI models trained only on public or commercially licensed content—never on client data.
Rigorous Quality Assurance
Dual-layer process combining automated testing with human clinical validation by subject matter experts.
Frequently asked questions
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