Regulatory alignment
Our platform aligns with international and regional GxP requirements—from GMP to GCP—across regulated workflows.
Built to help regulated teams use AI with confidence—through human oversight, traceability, and operational controls.
At Narrativa, compliance is built into how we develop and operate AI. Our platform is designed for life sciences, healthcare, and other regulated environments—helping teams work with confidence while maintaining oversight, traceability, and control.
From Good Manufacturing Practice (GMP) to Good Clinical Practice (GCP), our platform supports the processes and controls regulated teams need to produce reliable, reviewable work.
Our platform aligns with international and regional GxP requirements—from GMP to GCP—across regulated workflows.
Keep generated content connected to its source information so teams can verify, attribute, and review the work.
Keep qualified experts in control of review and approval. AI supports the work; people remain accountable for decisions.
Narrativa’s AI solutions are tailored for pharmaceutical, biotechnology, and healthcare teams. Built-in capabilities help organizations apply oversight throughout the content lifecycle—from drafting through review.
Support validation activities and processes for AI-enabled workflows.
Make activity and content changes easier to follow and review.
Help ensure people can access the tools and information appropriate to their role.
Keep domain experts involved in checking accuracy, context, and regulatory fit.
Trustworthy AI depends on transparency, accountability, and continuous attention. These principles guide how we select, evaluate, and use AI across our solutions.
Make AI-generated work explainable and traceable, with data lineage maintained throughout the process.
We adhere to GDPR, HIPAA, and other relevant data-protection laws, with secure model hosting, encrypted processing, and regular vulnerability assessments.
Subject outputs—especially in medical writing and regulatory contexts—to expert human review.
Continuously evaluate models for potential bias and suitability for sensitive use cases.
A cross-functional AI Governance Committee oversees implementation and reviews evolving standards and practices.
Evaluate commercial and open-source language models through internal protocols to assess suitability for sensitive domains.
Use feedback, regulatory developments, and advances in technology to keep our approach current.
Strong compliance supports the quality, reliability, and safety of every outcome—helping reduce risk, accelerate approvals, and give teams greater confidence in AI-assisted work.
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