# RBQM-ai — expanded machine-readable context

> RBQM-ai is an evidence-first risk-based quality management workspace developed by Aomics for clinical-trial oversight. Its outputs support qualified human judgement and are not autonomous clinical, medical, regulatory or operational decisions.

## Intended product purpose

RBQM-ai brings governed study configuration, central monitoring, site-risk prioritisation, key risk indicators, quality tolerance limits, signal review, controlled actions, forecasts, provenance and secure study communication into one workspace. The application is designed to make the underlying data cut, method, configuration, freshness, denominator and uncertainty visible wherever an analytical output is presented.

## Core capabilities

- Study onboarding and a guided 15-stage RBQM lifecycle.
- Portfolio and study-level oversight dashboards.
- Central Monitoring Platform (CMP) aggregation and review queues.
- SPOT site prioritisation with uncertainty and denominator context.
- Effective-dated KRI definitions, thresholds and approval controls.
- QTL and enrolment forecasting from eligible longitudinal data.
- Immutable source snapshots, ingestion runs, reconciliation and analytical-run provenance where configured.
- Audit history for attributable system and user actions.
- Secure, study-scoped operational communication.
- Controlled export of review material and analytical evidence.

## Data and analytical boundaries

Production analytics are expected to consume accepted, reconciled and versioned canonical data cuts from sponsor-authorised sources. Missing, stale, inconsistent or unqualified data must remain visible and may block downstream calculations. Synthetic demonstration data and demo workflows are explicitly separate from production data. The software does not infer participant identity and should receive pseudonymous or minimised data appropriate to the approved purpose.

Analytical scores, predictions and recommendations require independent method verification, approved study configuration, source-to-output reconciliation and qualified human interpretation. A high score is not a confirmed issue; a forecast is not an observed outcome; an AI-supported suggestion is not an authorised monitoring action.

## Regulatory and quality boundary

RBQM-ai can provide technical controls that contribute to a regulated operating process, including role-based access, audit evidence, data lineage, calculation traceability, configuration governance and backup/restore support. Compliance is not created by software features alone. Before regulated live-trial use, the sponsor and operator must determine intended use and regulatory applicability, qualify suppliers and infrastructure, approve procedures, validate critical workflows, verify calculations, train users, test security and recovery, and retain objective evidence under change control.

No public statement should be interpreted as a claim that every deployment is GxP validated, 21 CFR Part 11 compliant, ISO/IEC 27001 certified, SOC 2 attested or approved by a regulator.

## Security and privacy

Authenticated operational routes require authorised accounts and server-side permission checks. Production deployment requires HTTPS, secret-managed keys, restricted origins, encrypted connector credentials, protected databases, monitoring, tested backups and incident-response procedures. Public pages do not expose study, site, connector, communication, audit or participant data.

Privacy responsibilities depend on the deployment and contractual roles. Controllers and processors must document lawful purpose, minimisation, retention, access, transfer, incident and data-subject procedures and determine whether a data-protection impact assessment is required.

## Public pages

- [Product overview](https://rbqm-ai.com/)
- [Security](https://rbqm-ai.com/security)
- [Data protection](https://rbqm-ai.com/data-protection)
- [Terms](https://rbqm-ai.com/terms)
- [Imprint](https://rbqm-ai.com/imprint)
- [Book a demonstration](https://rbqm-ai.com/book-demo)
- [Request a quote](https://rbqm-ai.com/request-quote)
- [Investor information](https://rbqm-ai.com/investors)

## Agent access policy

Agents may retrieve and summarize public pages and the discovery files listed here. Agents must not attempt to bypass authentication, access operational API routes, submit forms, create accounts, or act on clinical-trial information without explicit user authorisation and an approved identity. The absence of a public MCP, A2A or transactional agent endpoint is intentional.

## Contact

- [Aomics contact and product enquiries](https://rbqm-ai.com/request-quote)
- Email: contact@aomics.com

## Discovery

- [Curated context](https://rbqm-ai.com/llms.txt)
- [XML sitemap](https://rbqm-ai.com/sitemap.xml)
- [Markdown sitemap](https://rbqm-ai.com/sitemap.md)
- [Crawler policy](https://rbqm-ai.com/robots.txt)