Protocol configuration
Institutions configure which protocols, prompts, and fields are active. Configuration is versioned and reviewed; it is not modified by the platform at runtime.
protocol.vprompt.setfield.mapreview.gate
In plain words
datasyteAI™ in a few short answers.
The platform behind AiMediQ™. It brings clinical context together, applies the hospital's own protocols, and coordinates what the team sees.
datasyteAI™ · platform
The intelligence layer behind AiMediQ™.
datasyteAI is the platform that synthesizes clinical context, applies institution-configured protocols, and coordinates the workflow surfaces used by AiMediQ™ — a clinician-in-the-loop system, not an autonomous one.
datasyte.stackgovernance · spans
- L5Clinician-facing surface & documentation05
- L4Support & orchestration04
- L3Protocol & configuration03
- L2Context synthesis02
- L1Approved inputs & context01
context → orchestration → workflow → documentationconceptual
Platform architecture
Five layers, one governed stack.
datasyteAI is organized as five coordinated layers wrapped by a shared governance rail. Each layer has a defined scope; the boundary between layers is where governance is enforced.
tick · 01 → 05conceptual · not a live system view
Conceptual architecture diagram. Sensitive implementation details are not disclosed publicly.
Capability · L2
Context synthesis, in the time between actions.
Assembles a structured, time-bounded view of an event from approved inputs so the clinical team can maintain situational awareness during a resuscitation.
event window · t₀ → now
Calculation assistance
Provides structured inputs for time-based calculations that clinicians commonly perform under pressure. Values are confirmed by the clinician before use.
calc.inputawaiting confirm
weight_kg—interval_s—dose_refprotocol.v
Concept visualization · deidentified
Clinician confirms every value. The platform never executes on the patient.
Digital scribing
Captures time-stamped actions and observations aligned with resuscitation documentation fields, reducing post-event reconstruction load.
Capability · post-event
Event analytics for debrief, QA, and registry reporting.
Prepares deidentified, institution-scoped summaries to support debrief, QA, and registry reporting workflows.
deidentified
by default
scope
institution
retention
per deployment
t₀event.windowdebrief
Conceptual timeline · deidentified · not a live view
Governance model
Clinician-in-the-loop, always.
datasyteAI is designed to support qualified clinicians and never to replace them. Governance is a property of the architecture, not an afterthought.
- Clinician-in-the-loop by design
- The platform issues no autonomous clinical actions. Every prompt, calculation, and summary is reviewed and confirmed by a qualified clinician who retains decision authority.
- Scope discipline
- datasyteAI supports coordination, documentation, and structured summaries. It does not diagnose, prescribe, dose, or issue treatment recommendations.
- Auditable behavior
- Prompts, configuration, and event capture are recorded to support internal review, QA, and — where applicable — regulatory conformance.
Integration & deployment
Verified, planned, and conceptual — labeled honestly.
Integration items are labeled to distinguish what exists today, what is on the roadmap, and what remains a design exploration.
- Verified
Institutional identity providers
Designed to integrate with standard institutional identity systems; specific providers confirmed per deployment.
- Planned
Clinical documentation systems
Structured event data is being prepared for downstream integration with institutional clinical documentation workflows. [CLAIM REQUIRES APPROVAL — specific systems pending.]
- Planned
Registry & QA reporting
Reporting formats and endpoints will be confirmed with pilot partners and registry stakeholders.
- Conceptual
Federated multi-site coordination
A multi-site coordination pattern is under design exploration. Not offered as an available capability.
Model operations
Versioning, monitoring, and change control.
A short summary of the documented practices we operate today. Detailed procedures are shared with institutional partners under appropriate confidentiality.
- 01
Versioning
Models, prompts, and protocol configurations are versioned. Each production surface is traceable to a specific reviewed version.
- 02
Monitoring
Operational metrics — availability, latency, and configuration state — are monitored. Clinical-outcome monitoring is scoped to the institution's evaluation plan.
- 03
Change control
Changes follow a defined internal change-control process with review, testing, and staged rollout appropriate to the surface being changed.
- 04
Incident handling
Defined internal procedures cover triage, communication, and remediation. Institution-specific escalation paths are agreed as part of deployment.
Scope note. This overview describes practices, not regulatory conformance. Any claim of regulatory clearance, authorization, or approval is limited to what appears in the approved regulatory-status statement.
Security & data handling
Data minimization, governed by design.
Security and privacy are institutional decisions. Our role is to provide a platform that respects them by default.
Full Security & Privacy overview- data.minimization
Data minimization
Only fields required for the supported workflow are collected. Free-text and identifying information are avoided where structured fields will do.
- handling.governed
Governed data handling
Data handling, residency, and retention are defined per deployment with the institution's privacy and security teams.
- training.gated
No learning from patient data without approval
The platform does not train or fine-tune models on patient data outside of an explicit, approved research and privacy arrangement with the institution.
datasyteAI — technical FAQ
Find answers to common questions about our technology and services
Next step
Bring datasyteAI into a technical conversation.
Request a technical briefing to walk through architecture, integration patterns, and governance with your clinical, IT, and compliance stakeholders.