Emergency & acute care
Prioritize the queue with explicit urgency signals so teams can align attention with clinical risk—not just arrival order.
AkaratImaging intelligence that meets clinicians in their workflow.
Clinical-grade AI for chest X-ray and CT—structured findings, triage signaling, and FHIR-ready output you can wire into the EHR. Built to augment radiologists and frontline teams, not replace them.
From Beast Innovations · interoperable, deployment-aware imaging AI.
Second-reader intelligence
Modalities
Chest X-ray, CT, radiology imaging
Turnaround
Structured insights in under 60 seconds
Output
FHIR R4 · LOINC · SNOMED
Deployment
On-premise or isolated cloud
What Akarat does
Akarat is a radiology decision-support layer: it analyzes imaging studies, highlights suspected findings, applies triage logic, and packages results in formats your systems already understand—so adoption is an integration problem, not a culture clash.
Fast structured reads
Turnaround measured in seconds for the AI pass—so teams can act on machine time while humans set the clinical narrative.
Physician in the loop
Outputs emphasize ranked impressions and explicit uncertainty—designed for sign-off, not silent automation.
Hospital-ready delivery
APIs and FHIR R4–oriented artifacts meet enterprise expectations for security, tenancy, and interoperability.
Built for real imaging workloads
Akarat targets the operational gaps that show up in everyday radiology—where volume, urgency, and complexity intersect.
- Capacity pressureDemand for imaging reads often outpaces available radiologist time—especially in emergency and high-volume departments.
- Delayed readsBusy workflows can stretch time-to-report, slowing treatment decisions when minutes matter.
- Cognitive loadFatigue and throughput limits increase the risk that subtle or concurrent findings receive less attention than they deserve.
- Critical findingsConditions such as pneumothorax, pulmonary edema, and significant masses benefit from earlier visibility in the queue.
Platform capabilities
A single pipeline from study ingestion to triage, structured reporting cues, and coded output—so downstream systems receive consistent, reviewable artifacts.
Triage paletteREDORANGEYELLOWGREEN
Detection & triage
- ·14+ chest pathology signals—including pneumonia, atelectasis, cardiomegaly, pleural effusion, and nodules
- ·Color-coded triage (RED / ORANGE / YELLOW / GREEN) to surface cases that need attention first
- ·Composite clinical syndrome views—acute chest, CHF, infectious patterns, malignancy-related signals, and more
Clinical alignment
- ·Nodule follow-up guidance informed by Fleischner Society protocols and Lung-RADS-style stratification
- ·ACR-aligned critical result alerts with structured severity (CRITICAL / WARNING / INFO)
- ·Ranked differentials and confidence context—the physician remains the decision-maker
Integration & standards
- ·FHIR R4–compatible artifacts for EHR and interoperability paths
- ·LOINC and SNOMED-oriented structuring for downstream clinical systems
- ·Secure API services designed for real hospital environments—not lab demos
How it fits your stack
Three clear stages—so clinical engineering, PACS administrators, and medical leadership can reason about responsibility boundaries and validation scope.
- 1
Ingest
DICOM studies enter your approved path; anonymization options keep identifiable data out of model processing when required.
- 2
Analyze
Specialized imaging models (including DenseNet121, MONAI, and TorchXRayVision–class stacks) score findings and assemble a structured draft.
- 3
Deliver
Clinicians receive triage cues, a concise case-oriented summary, and interoperable output to document review in the EHR.
Akarat is decision support: it does not issue final diagnoses. The treating clinician integrates AI output with history, physical exam, labs, and judgment—preserving accountability and regulatory clarity.
Security, privacy & governance
Healthcare data demands zero-excuse controls. Akarat is designed around encryption, access governance, anonymization paths, and standards-based exchange—so procurement and information security teams can map it to their frameworks.
- On-premise deployment: images and reports can remain entirely inside your network boundary
- Encryption in transit and at rest across the supported deployment models
- DICOM anonymization pipeline before AI processing—designed so identifiable patient data does not enter the model path
- Role-based access control with audit logging for traceable access
- FHIR R4 alignment for standards-based exchange with hospital systems
- Architected with KVKK, GDPR, and HIPAA-oriented control patterns in mind
Where cloud hosting is preferred, workloads run in isolated, single-tenant-style configurations without cross-institution data pooling. Model improvement on customer data requires explicit institutional consent—never assumed in default terms.
Who gets the most from Akarat
Same core engine—different primary buyers. Position the rollout where urgency, volume, or coverage gaps are clearest.
Radiology & imaging departments
Add a consistent pre-read layer with structured language, freeing specialists to focus on interpretation, protocol decisions, and complex cases.
Hospital IT & security
Meet stringent data residency expectations with on-prem or single-tenant cloud options, encryption, RBAC, and audit trails.
Regional & referral networks
Extend decision support where subspecialty coverage is thin—same standards-backed output, tuned for your governance model.
See Akarat on your studies and integration path.
We will walk through deployment models, validation expectations, and how Akarat maps to your PACS, EHR, and governance requirements—no generic deck, just product and engineering detail.
Akarat is developed by Beast Innovations. Availability and regulatory status vary by region—confirm with us for your market.