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Transform the way you build, validate and submit studies

Verisian uses traceability-enabled AI to reimagine clinical programming and guarantee a high level of integrity in submissions.
Based on graph theory

Full study traceability

Verisian is based on a knowledge graph derived from a study's source code. No black boxes, hallucinations, and everything is fully reproducible.
Code to Graph
Verisian transforms code and logs into a knowledge graph allowing you to understand every line of code, its content, manipulations and interdependencies. This makes any transformation fully traceable to find all upstream dependencies and downstream effects.
Macro Traceability for Analysis
Verisian uses MPRINT statements from SAS logs to resolve any macro invocation and variables to make macros fully traceable and help you debug your analysis based on exactly what was executed. This ensures full traceability with dependencies and downstream effects instantly visible.
Enhanced Study Transparency
You'll be able to understand your study at different levels of abstraction, from how datasets depend on each other across libraries and files to the original code. This facilitates everything from easier onboarding to enhancing the transparency of regulatory reviews.
Empowered by AI

Deploy Clinical AI Co-pilots

Verisian's AI co-pilots help you to produce analyses faster and are designed to guarantee accuracy.
AI Co-pilots
Verisian offers AI co-pilots that can write and debug code, produce documentation and design analyses. These co-pilots can also be tailor made by training them on company or indication-specific derivations to understand exactly how you analyze clinical trials.
AI Built on Traceability
Verisian's AI uses deterministic graph theory-based technology to validate ouputs and establish context for the co-pilot prompts, making the outputs more likely to be specific and correct. They are built using our extensive traceability and code manipulation technology.
Enhanced Study Transparency
Using AI co-pilots to generate code and documentation moves the bottleneck from generation to quality control. That's why we've built a Validator that serves as a quality gatekeeper against which you can develop and makes sure that no hallucinations escape your notice.
Coming soon


Build faster and higher quality studies through automation
Reuse validated code across studies to build SDTM, ADaM and TLFs faster
Use libraries of code templates derived from existing studies and filter by indication, study and more.
Speed up and improve accuracy of SDTM, ADaM and TLF development through the reuse of validated code.
Leverage Verisian's code-based traceability to identify required template dependencies and highlight which are missing.
Leverage AI to write better code, auto-generate documentation and debug faster
Use bespoke models to generate code and documentation tailored to your organization and study.
Optimize code for readability, maintainability, consistency, and robustness.
Understand unfamiliar code and suggest bug-fixes.
Develop in confidence with traversable dataset and variable-level traceability
Quickly navigate and understand upstream dependencies.
Focus on coding while the develop in confidence features tracks unmet upstream requirements and downstream effects for later review and resolution.
Know when a template's dependencies are present, and exactly what is missing if not.
Debug in confidence to ensure continuous quality as you develop
Proprietary log message classification algorithms cluster log messages by common cause.
Debug what is executed by leveraging macro resolution.
Leverage full traceability spanning datasets, variables, formats, and codelists to find and fix root causes.


Safeguard quality in your submission through automated quality control
Leverage full study traceability for faster Log QC and issue resolution
Review, debug and fix root causes by leveraging full study traceability spanning code, associated log messages, datasets, formats and codelists, filtered by file or datasets based on what was actually executed.
Proprietary log extraction and analytics algorithms with macro resolution.
Proprietary log message classification algorithms based on traceability and code understanding.
Streamline log resolution by grouping log messages with shared root causes based on traceability, allowing a single fix to clear multiple log messages
Continuously compare production and validation programming to ensure programming validity
Proprietary automated program-comparison and real-time scoring algorithms summarized in a dashboard.
Scoring separated into three categories: passed, review required, and rejected.
Review comparisons on code and traceability level.
Review and resolution process with full audit-trail.
Ensure analysis robustness and integrity through traceability
Proprietary code diagnostics for robustness, transparency, consistency, and integrity summarized in a dashboard.
Ensure code is transparent so that it is easily understood, maintained, and extended.
Ensure code is robust to handle data changes and quality issues.
Automate and monitor SAP/Specification implementation adherence
Compare specifications with code implementations using traceability and traceability-aware AI.
Comparisons separated into three categories: passed, requiring review, and rejected.
Review adherence scoring efficiently using full traceability.
Review and resolution process with full audit-trail.
Coming soon


Be confident your study is submitted with full integrity, transparency and trust
Build trust with reviewers and improve transparency through an analysis fitness score
Aggregate study analysis fitness score across Log QC, double programming validation, analysis integrity, and SAP adherence.
Dashboard for internal and optional regulatory review.
Export report to PDF or HTML for internal or regulatory review.
Review what's true
Reviewers review what was actually executed (macro resolved), in which sequence, and how programs were nested.
All execution logs are transformed into a single executable program covering the full study to enable reproducibility.
Be continuously submission ready through automated define.xml updates
Auto-fill tricky parts of SDTM, ADaM, and ARM define-xmls based on traceability analysis.
Be aware and efficiently review edge cases.
Guarantee reporting integrity by extraction and reporting from the source-of-truth: executed code.
Save time, prove integrity and establish trust with regulators
Build trust through an analysis fitness dashboard review mode for regulators.
Prevent and speed up inquiry-response cycles through a Full Study Traceability review mode for regulators.
Provide access to an automated study-specific question-answering system using AI to translate traceability information to natural language.

Get started now

Get started today with Verisian using our free trial, or get in touch with us to learn more. We would love to hear from you.