QxAIOS keeps each workflow run connected to its inputs, execution context, review actions, and evidence, so teams can review decisions with confidence and retrieve meaningful records during audit or quality review.
Governed AI operations for GMP quality teams
Deploy GMP-ready AI agents with Quality Compliance by Design
Design, govern, and operate regulated AI workflows on one platform, with controls built for strict compliance environments to ensure patient safety.
GMP Production Ready
Automated, tested and validated deployments
Compliance by Design
Follow industry leading good practices
Audit Ready
Every decision documented
Why This Works
The governance questions should come first. The platform and delivery model are built to answer them.
Platform & Discipline
Microsoft provides the platform. QxAIOS and QxAIOPS provide the discipline.
The technology base matters, but so does the way it is configured for controlled use. We use Microsoft Azure and agent tooling as the foundation, then apply governed workflow design and delivery discipline for regulated quality operations.
Platform
A platform base regulated teams can assess with confidence
QikSolve is a Microsoft partner and builds on Microsoft Azure, Microsoft AI services, and Microsoft Agent Framework tooling. For non-technical stakeholders, that means the solution starts on an enterprise technology base that is already familiar to many regulated organisations and easier to assess as part of a GAMP-style platform review.
- Known enterprise foundation: the solution is built on Microsoft cloud and AI services that many organisations already understand from a security, operations, and supplier perspective.
- Easier platform assessment: instead of evaluating an unknown stack from first principles, teams can assess how a recognised technology base is being used, configured, and controlled.
- Stronger fit for validation planning: a stable platform foundation makes it easier to focus validation effort on workflow design, intended use, and control strategy rather than platform invention.
Discipline
Governed configuration for GMP-regulated use
QxAIOS and QxAIOPS add the control layer that makes the platform usable in GMP-regulated quality settings. QikSolve has worked in GMP software for more than 10 years alongside industry experts and quality leaders, and that experience shapes how workflows are designed around controlled inputs, mandatory review gates, evidence expectations, validation discipline, and change control thinking rather than leaving those obligations to be solved later.
- Pre-governed foundations: teams start with workflow patterns designed for controlled execution, accountable review, and audit-ready evidence capture.
- Good practices built in: validation intent, review checkpoints, data integrity expectations, and controlled change principles are considered from the start rather than added after deployment.
- Regulatory understanding in the workflow: the design approach reflects how regulated teams need to preserve ALCOA+ style evidence, manage change under governance, and maintain human accountability over AI-assisted decisions.
Message House
Controlled AI operations for GMP, built for real delivery
QxAIOS combines platform foundations, governed workflow design, validation discipline, continuous improvement, and GMP quality accountability.
Platform Foundation
A governed operating layer for AI-enabled quality workflows, built on Microsoft Azure and AI services.
Governed Workflow Design
Controlled inputs, review gates, and evidence expectations are configured from the start.
Validation and Evidence Discipline
Testing, evaluation, validation, and reporting are built into delivery so teams can detect issues early and improve with control.
Quality Accountability for GMP
AI supports the workflow, but GMP quality ownership, review approval, and change control stay with the quality function.
Proof Signals
What teams can see in practice
Evaluation Outcomes
Teams can review structured evaluation outcomes to see where an agent is performing well and where intervention is needed.
Validation Records
Validation activity can be captured as delivery evidence, supporting readiness checks before workflows move forward.
Review Decisions
Human review outcomes can be recorded alongside workflow execution so approval and intervention are visible.
Input and Grounding Trace
Output reports can include the inputs used, the grounding context applied, and the evidence attached to the response.
Controlled Data Scope
Data exposure is deliberately constrained so teams can see what the agent had access to and what it did not.
Continuous Improvement Loop
Continuous testing and evaluation help surface reliability or compliance issues earlier, creating a practical feedback loop to improve both agent intelligence and workflow design.
Case Study Journey
How QxAIOS and QxAIOPS were used to move from manual paper/digital processes to controlled agentic AI
This case study shows the practical sequence: establish controlled boundaries with QxAIOS, then implement and govern delivery with QxAIOPS.
1. Price Pressure Arrives First
ReachedA pharma-industry company faced stronger international competition and tighter pricing while still running a mixed paper-and-digital operating model. The business needed to improve throughput and consistency without eroding GMP control.
- Manual document movement and fragmented digital tracking made cycle times hard to predict.
- Quality and operations teams were spending disproportionate effort preparing and reconciling evidence.
- International competition
- Margin pressure
- Need for higher throughput
2. Paper Workflows Start to Hurt
UpcomingThe pain point was not only paper. It was the combination of paper records, disconnected digital steps, and inconsistent review pathways that created friction across operational processes.
- The same information was being checked multiple times in different formats with limited reuse of prior review work.
- Exception handling was highly person-dependent, which increased variability and slowed escalation decisions.
- Manual handoffs
- Review bottlenecks
- Evidence prep overhead
3. Boundaries and Ownership Come First
UpcomingBefore any agentic capability was introduced, QxAIOS was used to define controlled operating boundaries: explicit scope, controlled inputs, clear role ownership, and non-negotiable human approvals.
- Each process was decomposed into assistive tasks where AI could support interpretation without taking approval authority.
- Escalation and override conditions were defined up front so decision accountability remained with qualified roles.
- Bounded scope
- Named owners
- Mandatory escalation
4. Controlled Agentic Integration
UpcomingQxAIOPS was then applied to implement controlled agentic integration through stage gates, versioned prompts/configuration, validation checkpoints, and traceable release pathways.
- Execution and review roles were segregated so an executing agent never served as its own reviewer.
- Evidence-first outputs were structured to show source context, rationale, and review actions rather than only conclusions.
- Stage gates
- Versioned configuration
- Human-in-the-loop
5. Go-Live with Governance Intact
UpcomingGo-live proceeded only when readiness evidence met release criteria, then shifted into continuous governance with monitoring, exception review, controlled change, and periodic requalification.
- Operational teams had a governed path for updates instead of ad-hoc prompt or workflow drift.
- Post-go-live oversight focused on both performance and compliance integrity, not speed alone.
- Readiness evidence
- Exception review
- Controlled change
6. Outcomes You Can Feel
UpcomingThe result was a measurable shift from fragmented paper/digital execution to controlled agent-assisted operations with stronger traceability, faster review preparation, and more consistent operational decision governance.
- Teams reduced repeated manual review effort while improving confidence in what evidence was used and why decisions were made.
- The operating model scaled more safely because controls were embedded in both design and delivery, not bolted on later.
- Clearer traceability
- Faster review readiness
- Consistent governance
Build or Partner
You can build this capability internally. Or you can start from a governed foundation.
A GMP-ready AI operating model is achievable, but the platform, control, and validation effort is substantial. The decision is not whether it can be done. It is how much time and internal capacity you want to spend building the control layer yourself.
Trusted Delivery Base
Microsoft Partner
QikSolve delivers on a Microsoft-aligned foundation, bringing regulated workflow design and delivery discipline to enterprise Microsoft environments.
Platform Choice
Built with Microsoft Azure and AI Services
The solution approach uses Microsoft Azure and AI platform services to support controlled, traceable AI workflows in regulated operating contexts.
Building it internally
- Define governance policies, quality gates, and review responsibilities for each workflow.
- Design and validate evidence, reporting, and traceability patterns.
- Implement security, escalation, testing, and controlled change processes.
- Maintain validation evidence and continuous improvement over time.
Working with QikSolve
- Governed platform patterns and quality-gate discipline are already in place.
- Evidence, evaluation, and reporting models are designed for controlled environments.
- Security, escalation, and delivery controls are built into the operating approach.
- Your team can focus on high-value quality workflows instead of platform invention.
Contact Route
Bring your highest-value quality workflow and the constraints around it.
We will map it to a governed delivery path, identify the control and validation considerations, and make the next conversation practical instead of speculative.
QxAIOPS keeps delivery credible after the first discussion.
If you already know the process area you want to improve, explore quality applications first.
What to Bring
Share the workflow you want to improve, the control concerns you need to manage, and any regulatory or validation constraints already in view. We will respond with a clear next step.
Open the Contact Form