Make the Work Clear
Define the request, owner, inputs, dependencies, deadline, and meaning of done before work begins so teams and tools are working toward the same result.
Regulated Industry Infrastructure
From Clear Work
to Verified Results
Important work is often spread across email, documents, project tools, and AI conversations. Aregis technology keeps a trail from the request and the allowed sources through the work, the review, and the decision.
How the Technology Works Together
Aregis uses GAME Plan to define and track the work on an engagement. Saga Agent can help complete clearly bounded tasks. Convergence can compare the result with the original requirement. A qualified person remains responsible for review and approval.
Used together, GAME Plan and Saga Agent leave a trail. GAME Plan holds the work: the request, the owner, the sources that were allowed in, the review, and the decision that closed it. When Saga Agent is used on a bounded task, the actions it took and the sources it used join that same trail. Sensitive information stays limited to the task, and a qualified person still accepts the result. GAME Plan is available now. Saga Agent is in active testing on real projects and joins the trail as it is brought into client engagements.
AVAILABLE NOW
GAME Plan
GAME Plan is available now. Aregis uses it to run an engagement: define the work, assign ownership, show dependencies, track progress, and record the evidence that demonstrates completion.
- Clear work, ownership, and priorities
- Visible dependencies, decisions, and risks
- Milestones linked to proof of completion
ACTIVE TESTING ON REAL PROJECTS
Saga Agent
Saga Agent is being tested on real projects. It matters because AI can move quickly but needs clear boundaries, approved sources, visible actions, and human review.
- Clearly assigned and bounded tasks
- Sources, actions, and results kept visible
- Human review before accountable use
ACTIVE TESTING ON REAL PROJECTS
Convergence
Convergence is being tested on real projects. It matters because producing an answer is not the same as proving that the requirement was met. Convergence helps identify missing evidence and supports a clear human review decision.
- Compare results with stated requirements
- Identify gaps, conflicts, and missing evidence
- Support rather than replace human approval
What the Technology Is Designed to Deliver
The value is not AI for its own sake. It is clearer work, stronger records, useful automation, and better control of sensitive information.
Keep the Evidence Connected
Keep a trail of sources, decisions, reviews, changes, and proof of completion with the work as it happens, instead of rebuilding that trail before an audit, submission, or customer review.
Use AI Under Human Control
Give AI a bounded assignment, approved context, and visible review path. A qualified person remains responsible for accepting regulated work and important business decisions.
Protect Sensitive Data
Define what information may be used, who and which tools may access it, where it may go, how long it may be retained, and what activity must be recorded.
Workflows the Technology Supports
Aregis runs every engagement on GAME Plan today. The use cases below are in active engagement now, followed by other applications in development. Saga Agent and Convergence are in active testing on real projects and will be brought into client engagements as they begin.
In Active Engagement
Human-led work running now, with qualified people responsible for every decision.
Workforce Training on AI Use
Why it matters: People are already using AI at work, often without a clear rule for what is allowed, what data may go in, or how output is reviewed.
How it helps: Train staff by role on approved AI uses, data limits, review, recording, and escalation, with a completion record for each person.
See the use case →AI-Assisted Training System Deployment
Why it matters: Training has to stay current as procedures change, remediation lands, and new procedures roll out.
How it helps: Link training to the procedures, draft and update material with client-approved AI tools, and keep a completion record for each role.
See the use case →AI Opportunity Analysis for Sponsors
Why it matters: Sponsors are asked to use AI in quality and regulatory work before they know where it helps or where it should stay out.
How it helps: Review the sponsor's work, rank where AI would help, name where it should not be used, and record the decision to pursue or leave each opportunity.
See the use case →AI Policy and Procedure in the QMS
Why it matters: Once a sponsor knows where AI will be used, the quality system has to say how.
How it helps: Write the AI policy and procedures so approved uses, human review, change control, and records are defined before a tool goes into a process.
See the use case →Procedure-to-Standard Gap Matrix
Why it matters: When a process has to meet a standard, the useful question is which procedures cover which requirements, and where the gaps are.
How it helps: Map the procedures that run a process to the standard they must meet, then use the gap matrix to plan and track remediation.
See the use case →Complaint and CAPA Investigation Writing
Why it matters: Complaint and CAPA investigations have to be written from the source records, follow the governing procedure, and show why the conclusion, root cause, and actions fit.
How it helps: Write each investigation from sanitized sources, with a reference for each material statement, a traceable root cause and actions for CAPAs, and a record of the person who accepted it.
See both use cases →Other Applications in Development
Workflows Aregis can organize on GAME Plan now, where AI support is still being developed and tested.
Portfolio Priorities and Delivery
Why it matters: Leadership needs one view of projects, resources, risks, decisions, and deadlines to choose priorities with confidence.
How it helps: Bring the portfolio into one plan, establish ownership, manage dependencies, and keep delivery connected to business goals.
Program and Project Recovery
Why it matters: Important work that is late, unclear, or spread across teams loses momentum and accountability.
How it helps: Establish a practical plan, clarify decisions and responsibilities, surface blockers, and restore a reliable path to completion.
Technical Writing and Controlled Documents
Why it matters: Teams need to turn source material, expert input, and requirements into clear documents while preserving review history and source traceability.
How it helps: Define the document and required sources, assign sections and reviewers, track revisions and open questions, and retain evidence for final approval.
Regulatory Submission Management
Why it matters: Submission work draws from regulatory strategy, nonclinical, clinical, CMC, quality, and outside partners. Missing inputs and late changes can put the whole timeline at risk.
How it helps: Map submission sections to requirements, source documents, owners, reviewers, dependencies, questions, decisions, and approval evidence from planning through final assembly.
Quality Systems and Audit Readiness
Why it matters: Organizations often discover missing records, unclear ownership, or unresolved actions only when an audit or inspection is approaching.
How it helps: Track procedures, controls, training, deviations, CAPAs, changes, audit findings, and supporting records continuously so readiness becomes part of daily work.
Regulatory Change and Data Integrity
Why it matters: New requirements and data-integrity concerns can affect procedures, systems, training, suppliers, and active programs at the same time.
How it helps: Translate a change or finding into affected processes, owners, actions, validation needs, records, and follow-up checks while preserving the reasoning behind each decision.
Supplier and Contract Oversight
Why it matters: Contract terms, quality agreements, supplier commitments, changes, and performance evidence often live in separate systems.
How it helps: Connect obligations to owners, deliverables, due dates, approvals, changes, performance records, and escalation paths.
CMC and Manufacturing Coordination
Why it matters: Development, analytical, manufacturing, quality, and supplier work must remain consistent even when it is split across internal teams and external partners.
How it helps: Connect process and analytical work, changes, risks, partner deliverables, quality decisions, and submission content so teams can see where information is missing or inconsistent.
Clinical and Nonclinical Operations Monitoring
Why it matters: Studies, sites, vendors, and outsourced activities create milestones, deviations, data questions, documents, and handoffs that are easy to lose track of.
How it helps: Keep a shared view of study and site obligations, partner deliverables, deadlines, deviations, decisions, escalations, and supporting records.
AI and Digital Workflows
Why it matters: Manual or fragmented processes hide who owns each step, what went in, and what was reviewed.
How it helps: Turn the process into a clear workflow with defined inputs, owners, controls, records, and human review.
Protect Sensitive Data by Design
Regulated records, intellectual property, contracts, clinical information, manufacturing knowledge, and portfolio data require deliberate controls. Data handling is defined for each engagement rather than covered by one broad promise.
Use Only What Is Needed
Limit the project context to the information needed for the assigned work and keep unrelated client or company information outside the workflow.
Approve Access and Providers
Define which people, systems, model providers, credentials, and integrations may access project information before they are used.
Set Retention and Environment Controls
Confirm provider retention settings and determine whether the work requires restricted access, isolated infrastructure, or a client-controlled environment.
Keep Decisions and Activity Visible
Record important sources, actions, reviews, exceptions, and approvals so the organization can understand how a result was produced and who accepted it.
Current Capability and Product Roadmap
The readiness labels below distinguish what clients can use as a standard service today from technology being actively tested on real projects.
Available now
Expert-led engagements
Aregis provides scoped regulated-industry delivery and program-management services under defined engagement terms and authority.
Available now
GAME Plan project management
Aregis uses GAME Plan, available now, to run an engagement through structured priorities, dependencies, ownership, milestones, and evidence.
Active testing
Saga Agent
Bounded AI execution and evidence capture are being exercised on real projects to test reliability, controls, review, and practical value as they move into client engagements.
Active testing
Convergence
Evidence review against stated requirements is being exercised on real projects to test accuracy, exception handling, and human approval as it moves into client engagements.
Standard client availability will follow technical, operating, data-handling, and client-readiness checks informed by this real-project testing.
How the standard is developing →Technology Partners
Aregis licenses its execution engines rather than building them in-house, and the standard those engines implement is developed by other parties. That keeps the rules governing your project record from being set by the company delivering your project.
SagaHalla
Contributes the specification and its reference implementation to the standards working group, and is the lead licensing partner for the Saga Agent Architecture and GAME Plan Engine.
Norta DeSyCo
Contributes the methods behind Convergence, which checks a result against the original requirement, drawing on research in cross-organizational collaboration and smart-contract systems.
PraSaga Foundation
Hosts the DAO SagaStandards Working Group, where contributed specifications can be reviewed, changed, accepted, or declined through the group's process.