Responsibility map
Names the delivery lead, specialists, local parties, client contributors, accountable reviewers, approvers, and escalation route.
The process stays visible from source to approved deliverable.
Durability Labs is AI-native, but AI is secondary to accountable regulatory work. Every engagement is structured around named people, authoritative sources, controlled documents, clear review, and explicit approval roles.
Five controls travel with every work package.
The exact tools may vary with the client environment and jurisdiction. The control model does not.
Source register
Records the authority or approved client source, jurisdiction, access date, version, and the deliverable conclusions it supports.
Version and issue control
Tracks document versions, open questions, decisions, dependencies, comments, owners, due dates, and closure status.
Review and approval gates
Separates preparation from interpretation, regulated review, client approval, and any jurisdiction-specific sign-off required.
AI-use record
Documents permitted AI-assisted tasks, approved systems, source verification, human review, and any tasks from which AI is excluded.
AI assists the workflow. It does not own the decision.
Controlled AI assistance may support source retrieval, comparison, drafting, formatting, consistency checks, and quality-control tasks. Qualified professionals remain accountable for interpretation, review, and approval.
Permitted task
AI use is defined for the engagement and limited to tasks approved for the client data and environment.
Approved system
Confidential material is not entered into a tool unless the system and use have been approved in writing.
Source verification
AI-assisted factual statements are checked against authoritative sources and recorded in the work product.
Human accountability
AI does not make autonomous final regulatory decisions or replace required professional and client approvals.
Before confidential material is received.
- Permitted systems, transfer methods, and storage locations
- Assigned access roles and disclosed subcontractors
- Retention, deletion, incident, and escalation rules
- Data-residency or cross-border restrictions
- Permitted AI-assisted tasks and client approval responsibilities
Excluded from our delivery model
- Autonomous final regulatory decisions
- Unsupervised submission content
- Patient-identifiable data or individual safety cases
- Training public or shared models on client information
- Guaranteed approval, acceptance, or timeline claims
Questions buyers usually ask.
The answer may change by jurisdiction and work package. The responsibility to make it explicit does not.
Who makes the final regulatory judgment?
The proposal identifies the accountable reviewer and client approver for each regulated conclusion. Durability Labs does not assign final judgment to an AI system or leave the role implicit.
Can work be completed without AI?
Yes. AI use is task-specific and subject to written client permission. A work package can be configured without AI-assisted processing when the client environment or material requires it.
Who handles local representation or filing?
The responsible local party is named separately. When needed, Durability Labs may coordinate a qualified partner, but local representation and field activity are not presented as core in-house capabilities.
What does source traceability mean in practice?
Material conclusions are connected to identifiable authority or client-approved sources, including jurisdiction, access date or version, and the part of the deliverable they support.
Put the controls in the scope—not in a promise after kickoff.
We define the people, sources, systems, review path, client approvals, local-party requirements, and exclusions before the engagement begins.