Software

EMA

About EMA: EMA is a clinical software initiative focused on training-to-practice continuity, clinical realism, and non-extractive system design in mental health education and care.

EMA (Electronic Mental Health Application) is RSL's first applied software project, a clinical training simulator designed to bridge graduate education and professional practice in mental health counseling.

EMA is developed and operated under the ruha platform. ruha serves as RSL's public-facing clinical software brand, with its own trust surface and governance documentation.

The Problem: The Training Gap

Graduate counseling programs excel at teaching clinical theory, ethics, diagnostic assessment, and therapeutic modalities. But students rarely encounter the administrative reality they will face upon licensure:

• Referral coordination and intake logistics
• Audit-ready documentation practices
• Billing and insurance workflows
• Consent as a process, not a checkbox

The result: newly licensed clinicians spend 3-6 months learning systems they could have mastered during training. This "training gap" wastes institutional investment, disrupts professional formation, and delays competent independent practice.

The Solution: Training-to-Practice Continuity

EMA solves this through a single continuous system that serves both graduate training and professional practice. Students learn on EMA; upon licensure, they continue using EMA. The data substrate changes, but the workflows, interface, and professional habits remain constant.

This continuity is EMA's competitive advantage. Clinicians trained on EMA do not need to relearn a new system upon graduation. 2-4 years of training "muscle memory" transfer directly to professional practice.

Architecture: One System, Two Substrates

EMA operates on a single platform with two data environments:

Training Phase (Graduate Education):

• Synthetic data only (no PHI risk)
• Faculty orchestration of clinical scenarios
• Mandatory supervision integration
• Institution-held license (Clinical Ethical License)

Professional Phase (Post-Licensure):

• Real client data (PHI-compliant)
• Professional autonomy
• Same workflows and interface preserved
• Individual-held license (Professional Use License)

What changes at licensure: the data substrate.
What never changes: the workflows, the interface, the muscle memory.

Who EMA Serves

• Graduate counseling programs seeking clinical realism in training
• Faculty who need to orchestrate intake scenarios and documentation practice
• Students building professional habits before licensure
• Early-career clinicians transitioning from training to practice
• Solo practitioners and small group practices

EMA enters the market through institutional partnerships with graduate programs, then bridges to professional practice through continuity, not direct competition with established EHRs.

Licensing: CEL → PUL Transition

EMA introduces a licensing model that mirrors professional formation:

Clinical Ethical License (CEL), Training Phase:

• Institution-held (university is licensee)
• Student-protective safeguards mandatory
• Synthetic data only
• Supervision required

Professional Use License (PUL), Post-Licensure:

• Individual-held (clinician is licensee)
• Professional autonomy
• Real PHI allowed
• Same ethical constraints preserved

At graduation, students choose: continue with PUL subscription, or export all training data and exit. No automatic conversion. No vendor lock-in.

What EMA Does Not Do

• No analytics on clinical content
• No productivity scoring or engagement metrics
• No sale or secondary use of patient data
• No model training on clinical material
• No per-seat pricing that penalizes collaboration
• No data lock-in, full export at any time, self-hosting always supported

Current Status: EMA is in pilot validation with institutional partners. The platform is in staged use and stability observation, with new capabilities introduced only after demonstrating safe, predictable operation. Feature expansion requires stability earned through real clinical and training use. Growth is secondary to correctness.

For more information, see ruha.io.

RcSim

RcSim is a research-driven software framework developed to support exploration of recursive structure, coherence, and stability in complex systems.

RcSim is not a general-purpose AI system and is not designed to automate decision-making or replace professional judgment.

At present:

• RcSim is under active development
• Public APIs and SDKs are not yet released
• Documentation and governance are being finalized prior to distribution

When RcSim tooling becomes available, it will be released here alongside:

• Clear scope definitions
• Usage boundaries
• Supporting documentation
• Governance context

Design Principles

All RSL software follows a consistent set of principles:

• Human-in-the-loop by design
• No hidden optimization targets
• No surveillance or behavioral extraction
• Clear separation between research and application
• Explicit limits on use and transfer

Capability is never treated as sufficient justification for deployment.

Relationship to Other Projects

Some software projects developed by RSL may interface with external systems or platforms. These integrations are scoped carefully and reviewed for boundary alignment.

Software intended for training, clinical support, or research contexts is released incrementally and evaluated in real-world settings before broader availability.

Availability

When software releases or SDKs become available:

• They will be announced here
• Accompanied by documentation and governance materials
• Released without urgency or pressure to adopt

There is no mailing list or early-access program.

Questions

For questions related to software development or future releases:

[email protected]