Sold by: Incedo Inc
AI-powered requirements automation solution for life sciences organizations to accelerate Risk Evaluation and Mitigation Strategies (REMS) and clinical program delivery. Built on AWS, it converts complex source documents into structured, Jira-ready Epics, User Stories, Acceptance Criteria, and delivery artifacts.
Overview
Accelerate Delivery for REMS and Clinical Programs
Life sciences organizations managing Risk Evaluation and Mitigation Strategies (REMS), clinical programs, and regulated digital initiatives often spend significant time translating complex documentation into implementation-ready requirements. Regulatory documents, program specifications, SOPs, process flows, presentations, and screenshots must be interpreted, structured, reviewed, and converted into backlog-ready artifacts before delivery can begin.
Incedo AI-Native Requirements Generation Engine transforms this process by converting unstructured source materials into clear, standardized, and actionable requirements in hours instead of weeks. Acting as a business analyst in agent form, the solution helps teams accelerate planning cycles, reduce manual effort, and improve delivery readiness across regulated programs.
Why Traditional Requirements Processes Slow Innovation
Requirements generation in life sciences environments is often manual, document-heavy, and dependent on limited analyst capacity. Teams must review multiple source formats, reconcile inconsistent inputs, and manually draft Epics, User Stories, and Acceptance Criteria before engineering work can start.
This creates long planning cycles, inconsistent documentation quality, repeated clarification rounds, and slower time-to-market for critical programs.
How the Platform Creates Value
The platform ingests unstructured materials such as REMS protocols, clinical program specifications, PDFs, PowerPoint decks, screenshots, workflows, and business documents. AI agents analyze the content, identify business intent, map workflows, and generate structured delivery artifacts including Epics, User Stories, Acceptance Criteria, Definitions of Done, and Jira-ready backlog items.
Teams can review, refine, and approve outputs through governed workflows while maintaining traceability from source document to final requirement.
Built Using AWS Services
The solution is built on AWS and can leverage Amazon Bedrock for generative AI content creation and reasoning, Amazon Textract for document extraction, Amazon Comprehend for language understanding, Amazon SageMaker for custom models and optimization, Amazon S3 for secure document storage, AWS Lambda for workflow automation, Amazon OpenSearch Service for intelligent retrieval, and Amazon QuickSight for productivity and delivery analytics.
What This Enables
Organizations gain faster requirements generation, improved consistency across teams, stronger traceability, reduced dependency on manual BA effort, quicker backlog readiness, and scalable support for future regulated programs.
Why It Matters
With the right AI automation in place, life sciences teams can shorten planning timelines, reduce rework, improve collaboration between business and technology teams, and deliver compliant digital programs faster with greater confidence.
Highlights
- Converts REMS and clinical program documentation into structured, Jira-ready Epics, User Stories, and Acceptance Criteria.
- Acts as a business analyst in agent form—reducing weeks of manual requirements effort to same-day first drafts and rapid refinement.
- Built for regulated life sciences environments with traceability, governance workflows, and scalable support for future programs.
Details
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Delivery method
Deployed on AWS
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Support
Vendor support
For product support, implementation assistance, and technical inquiries, customers can contact the Incedo support team:
Website: https://www.incedoinc.com
Email: Partnerships_Alliances@incedoinc.com
Incedo provides support across platform implementation, document onboarding, workflow integration, AI tuning, governance setup, user enablement, and ongoing optimization.
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