Orchestral IQ
Orchestral IQ transforms healthcare data into intelligent action through advanced AI capabilities. Securely prototype and deploy healthcare-native AI agents, models, and automated workflows at scale.
Every AI algorithm is stored, versioned and audited in one secure workspace built on open standards.
Healthcare organizations spend millions on AI experiments that fail to reach production. Generic platforms can’t meet the strict requirements of clinical workflows, compliance, and PHI protection. The result: wasted investment, fragmented systems, and unrealised outcomes.
Orchestral IQ is built for healthcare from the ground up - secure, compliant, and ready for production from day one.
Features of Orchestral IQ
Pre-built healthcare AI agents - transform workflows with agents that are designed to understand the complexities of healthcare.
Low-code AI agent and workflow builder - rapidly create and customize AI agents.
Healthcare-specific prompt libraries – faster adoption and more accurate outputs with curated, domain-trained prompts.
Conversational AI assistants for data and clinical teams – simplify access to insights across the organization.
Health Data Model integration – AI results flow directly into patient records and data models.
Central algorithm repository - full version control and audit trails to meet compliance requirements.
PHI-protected large language models – secure by design, with patient health data safeguarded at every step.
Secure API endpoints - MCP support for easy integration, and seamless EHR connectivity to connect existing health records without costly or complex integrations.
Retrieval-augmented generation (RAG) - contextualized AI responses from vector indexed data.
How it works
The control center for healthcare AI
At the heart of Orchestral IQ is a secure, central AI repository - the control center for storing, versioning, and deploying large language models, AI agents, and workflows at scale.
AI processing flow
When data is submitted for processing, Orchestral IQ uses a series of components to ensure scalability and reliability:
API gateway authenticates incoming requests through a secure REST endpoint.
Load balancer distributes requests to the least-busy inference services.
Inference service reformats requests into an internal structure and manages them asynchronously, enabling multiple requests to run in parallel.
Queues and router / aggregator buffer and direct requests to the appropriate deployed model or algorithm.
Processor containers (Docker-based) execute the algorithm or ML model and generate results.
Results queues and response service route outputs back through the inference layer and return them via the API.
This asynchronous, queue-based design ensures requests are never lost, even if a service is temporarily unavailable, and allows the platform to auto-scale as demand grows. The runtime is orchestrated on Kubernetes for resilience and elasticity.
Model deployment and integration
Researchers and data scientists can prepare and upload models using code templates (Python, Java, or any supported language). Supporting artifacts like vocabularies, indexes, or configuration files are included to ensure models run predictably. Models trained with frameworks such as TensorFlow, Keras, and scikit-learn are supported out of the box. Register, train, and deploy algorithms, including:
Clinical calculators and tools.
ML models for prediction and forecasting.
Generative AI applications to draft, summarize, and classify.
Reasoning AI agents that use tools to execute complex workflows.
Models are deployed into runtime containers through the Processor Designer, exposing them via a secure ML/AI API endpoint. Data can be processed in three ways:
Single datasets via REST calls.
Batch uploads via SFTP.
Real-time streaming from applications.
Advanced AI capabilities
Orchestral IQ extends beyond model hosting with healthcare-specific AI infrastructure:
Prebuilt AI agents, workflows, and conversational chatbots that accelerate deployment.
Native support for large language models (LLMs), with options for local or cloud-hosted LLMs integrated inside the governance boundary.
Vector indexing and retrieval-augmented generation (RAG) to allow contextual responses based on health data.
Integration with the Health Data Model, allowing outputs such as risk scores or AI insights to be written directly into patient records (e.g., automated readmission risk calculations).
Governance and safety
Orchestral IQ is built with healthcare compliance in mind. Governance features include audit trails, model cards, and monitoring for model drift. Every request and result is logged, ensuring explainability and accountability. Role-based access, separation of design-time and runtime environments, and full audit capabilities protect PHI and PII throughout AI operations
AI healthcare applications & use cases
Healthcare AI agents
Manual data processing limits healthcare teams to reactive care. Orchestral IQ deploys AI agents that continuously monitor patient data, identify care opportunities, and trigger appropriate interventions.
AI agents operate within your data governance boundary using Model Context Protocol (MCP) integration. They can query data, use pre-approved tools and resources, and submit API requests while maintaining complete audit trails for clinical safety.
Healthcare agent capabilities:
Continuous patient data monitoring.
Care gap identification.
Population health analysis.
Medication safety and interaction checking.
Build your own with the agent builder.
Transform from reactive to proactive care management.
AI population & patient data management
Healthcare platforms generate massive amounts of data but limited actionable insights. Orchestral IQ automates data quality assessment, pipeline creation, and system monitoring to maximize your data’s clinical value.
AI automatically validates ingested data for inconsistencies between patient demographics and clinical records. Medication safety checks and drug interaction monitoring happen continuously, not just at prescription time.
Automated intelligence features:
Data quality assessment for clinical records.
Inconsistency detection across patient records.
Real-time medication safety monitoring.
Build your own with the workflow builder.
Spend less time managing data pipelines and more time improving patient outcomes.
AI generative interfaces
Static dashboards can’t adapt to changing clinical workflows. Orchestral IQ introduces generative user interfaces that create forms, visualizations, and workflows in real-time based on user context and data requirements.
Conversational AI provides an alternative to traditional applications. Clinicians can query patient data, generate reports, and access insights through natural language interfaces designed for healthcare workflows.
Generative capabilities:
Dynamic form creation based on clinical context.
Conversational AI for data access.
Real-time UI adaptation to user needs.
Natural language query processing.
Context-aware workflow generation.
Eliminate the friction between clinical teams and healthcare data.
Get started with Orchestral IQ
Why Orchestral IQ
Orchestral IQ goes beyond experimental AI, delivering operational advantages that make a measurable difference:
Always on – zero-downtime model updates keep services reliable 24/7.
Elastic by design – automatic scaling handles everything from routine loads to peak demand.
Flexible deployment – run AI your way: single dataset, batch, or live streaming.
Built-in resilience – automatic request recovery ensures continuity when workloads spike.
Multi-language support – serve diverse populations with algorithms built to operate across languages.
Secure integration – APIs designed to connect with clinical systems without security compromises.
Clinical decision support workflows – embed insights like risk scores and readmission predictions directly into workflows.
Ready to deploy healthcare AI that works?