AIRA is the secure, offline LLM framework embedded in the Aridhia Digital Research Environment (DRE), engineered to give healthcare researchers unparalleled control over sensitive data, uncompromising performance, and seamless integration.
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In today’s data-driven healthcare landscape, every patient record, genomic sequence, or clinical trial protocol represents not just information, but trust. Researchers demand powerful AI tools to accelerate discovery, yet can’t risk exposing Protected Health Information (PHI) or proprietary insights.
Aira—natively embedded in the Aridhia Digital Research Environment (DRE) —delivers truly offline large language model (LLM) inference, ensuring every byte of your sensitive data is processed only within your secure workspace, using the same OpenAI-style API calls your developers already know, and restricted by the Aridhia DRE’s RBAC controls, security, and governance features.
Aira is the secure LLM framework embedded in the Aridhia Digital Research Environment (DRE), engineered to give healthcare researchers unparalleled control over sensitive data, uncompromising performance, and seamless integration.
The Aira Framework isolates models and wraps them in the secure boundary of the DRE. This ensures that models are consistent, platform owner controlled and all prompts and inferences remain entirely within the scope of the DRE, ensuring no possibility of exfiltration to external services.
By design, Aira’s inference engine operates without any internet egress. No model telemetry leaves your Azure subscription, and no hidden “phone-home” calls occur—guaranteeing that PHI and proprietary research never stray from the Aridhia DRE.
Healthcare regulations such as HIPAA, GDPR, and local data residency rules mandate absolute control over patient data. Offline-only LLMs remove ambiguity: you know exactly where data lives, how it’s used, and that it never touches an external API.
Custom models trained on your unique datasets represent critical IP. When inference happens exclusively within Aira’s secure framework, you eliminate the risk of model or data leakage to third-party service providers.
Every inference job is logged in the DRE’s immutable audit trails. Offline execution provides a clear chain of custody for data and model usage—vital for internal governance, ethics boards, and compliance audits.
Utilise familiar GPT-style endpoints without rewriting applications.
Run models exclusively with the scope of your Aridhia DRE platform, no external AI service access.
Auto-scale GPU clusters and CPU pools on demand, balancing interactive and batch workloads.
GPU-accelerated batching and multi-model serving, prioritise and schedule models to support concurrency.
Assign priority tiers so mission-critical tasks pre-empt lower-priority jobs. Ensure model versions are retained and consistent, changing only when required.
Register and secure custom PyTorch, TensorFlow, or ONNX models in a centralised catalogue.
Secure, isolated AI opens up the possibility of using SLM and LLM technologies on sensitive data for research and analysis.
By design, Aira’s inference engine operates without any internet egress. No model telemetry leaves your Azure subscription, and no hidden “phone-home” calls occur—guaranteeing that PHI and proprietary research never stray from the Aridhia DRE.
Healthcare regulations such as HIPAA, GDPR, and local data residency rules mandate absolute control over patient data. Offline-only LLMs remove ambiguity: you know exactly where data lives, how it’s used, and that it never touches an external API.
Custom models trained on your unique datasets represent critical IP. When inference happens exclusively within Aira’s secure framework, you eliminate the risk of model or data leakage to third-party service providers.
Every inference job is logged in the DRE’s immutable audit trails. Offline execution provides a clear chain of custody for data and model usage—vital for internal governance, ethics boards, and compliance audits.
All data ingestion, storage, and inference occur inside the DRE’s locked-down Azure environment, benefiting from its mature policies, audit trails, and role-based access controls.
Point existing OpenAI clients at Aira’s compatible endpoints. Researchers and developers start working quickly with familiar APIs.
Leverage Azure’s elastic GPU and CPU pools through Aira’s dynamic scheduling. Assign priority tiers to workflows so that critical clinical queries always leap ahead in the queue.
Batch non-urgent jobs overnight, allocate spare GPU capacity to research workloads, and avoid idle hardware costs.
Contextualise prompts and API calls to further tailor results and improve the quality of responses and outcomes.
From global research networks seeking cures for the world's most threatening diseases to small research teams looking to make a big difference, our Trusted Research Environment can be scaled to suit the complexity of your research requirements.
A multi-tenanted SaaS trusted research environment, aimed at individual research teams and projects, with Workspaces hosted in the UK, US, EU, Canada and Australia.
A single-tenanted trusted research environment, aimed at larger enterprises and initiatives, which can be hosted in the Azure region of your choice.
