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CloudKites

Pencitraan asli-AI, di tempat layanan berlangsung.

AI klinis tepercaya yang dapat digunakan di lokasi atau hibrida — dimulai dari PACS asli-AI untuk pencitraan medis, berkembang menjadi asisten klinis beragen, dan akhirnya berwujud.

A clinician at a workstation reviewing medical imaging with AI assistance.

Dirancang untuk kepercayaan klinis

Empat prinsip menjadi dasar semua yang kami bangun.

Di lokasi atau hibrida
Terapkan pod di tempat yang Anda pilih — sepenuhnya di lokasi atau hibrida.
Berbasis standar
Mendukung DICOM, HL7, dan memperhatikan HIPAA, sesuai dengan sistem yang sudah Anda miliki.
Manusia dalam proses keputusan
AI membantu dan menyusun draf; klinisi meninjau dan menandatangani.
Alat gratis
AI klinis yang berguna untuk dokter umum dan untuk semua.

Two layers: the edge at the point of care, the pod behind it

CloudKites is an AI-native PACS built in two layers. Edge software assists healthcare workers in real time where care happens; the pod is the information system and archive behind it — deployable on-prem or hybrid by your choice.

The edge — EndoEdge, PathoEdge, TomoEdge — runs on the device where the work happens. It assists the clinician in the moment and captures the study as it is made: images, video clips, whole-slide images. Because it lives at the point of care, the assistance arrives at the pace of the procedure rather than the pace of a network, sitting quietly inside the moment instead of interrupting it. The clinician should never be waiting on the software; the software waits on them.

The pod — EndoPod, PathoPod, TomoPod — is the information system and archive: an EIS, LIS or RIS that organises the studies and their patient metadata, encapsulated as DICOM and aligned to HL7 with a HIPAA-aware posture. Where the pod runs is the customer's call. Keep it fully on-prem, so the archive and information system stay inside the facility; or run it hybrid, an on-prem pod paired with a cloud pod, with edge and cloud kept in sync asynchronously so studies are reachable wherever they are needed.

The same architecture flexes from a single small clinic to a medium-to-large hospital, and it is AI-assisted-ready: pluggable, extensible models plug in gradually for specific tasks and can be customised per customer. You turn on what helps and leave the rest. Whatever the deployment, the read ends the same way — a clinician reviews the AI-assisted draft, edits it and signs it. The edge and the pod do the carrying; the clinician keeps the decision.

An edge appliance at the point of care with the pod archive behind it.
consistent, every read
On-prem or hybrid — the same model, every deployment, with the clinician signing off.

Edge dan pod di seluruh endoskopi, patologi, dan radiologi.

Alat edge membantu secara real-time di titik layanan; pod adalah sistem informasi dan arsip — di lokasi atau hibrida, dengan AI yang dapat dipasang dan klinisi yang meninjau serta menandatangani.

  • EndoEdge + EndoPod — real-time endoscopy AI and a full EIS.
  • PathoEdge + PathoPod — whole-slide imaging and a pathology LIS.
  • TomoEdge + TomoPod — an AI-native RIS and PACS.

Jelajahi platform

Endoscopy Pathology Radiology CloudKites AI-native PACS Clinicianstays in control Findingsto the record

From capture at the edge to a signed report

From the moment a study is captured at the edge to the moment a report is signed, the path is the same across every modality — and a clinician is in charge at every point along it.

1 Capture 2 Sync 3 Review 4 Report
Capture at the edge → sync to the pod → review in the web viewer → sign the report.
A clinician reviewing an AI-assisted draft report before signing.

It begins with capture at the edge, on the equipment a department already uses. The edge tool assists in real time and records the study — and the patient metadata that belongs with it — into the local edge database. Nothing about the way a clinician works has to change for the assistance to be useful; the platform meets the existing instrument where it is rather than asking a team to adopt a new way of doing the job.

Then the study syncs to the pod — on-prem, and to a cloud pod too if you run hybrid — encapsulated as DICOM and aligned to HL7. The sync is asynchronous, so the edge never waits on the network, and the study becomes accessible in the web-based viewer wherever it is needed. Pluggable AI models, added gradually and customised per customer, screen systematically and draft a semi-automated report. They propose; they do not decide.

Review is where judgement lives. In the web viewer, the clinician brings context the study cannot hold — the patient, the history, the reason for it — and weighs the AI-assisted draft against it. Only after that human review is the report signed, as a structured result the next clinician can read and trust. Four steps, one principle running through all of them: the edge and the pod assist, and the clinician decides.

One idea, expressed across every place imaging is read

CloudKites is not a single app. It is a family — three edge-and-pod imaging products on a shared foundation, Myro the agentic assistant that works across the clinical routine, and a set of free tools that put genuinely useful clinical AI in anyone's hands.

At the centre sit three imaging products, each an edge tool plus a pod — EndoEdge and EndoPod for endoscopy, PathoEdge and PathoPod for pathology, TomoEdge and TomoPod for radiology. They look different on the surface because the work they support is different, but underneath they share one AI-native foundation and one model: real-time assistance at the edge, an information system and archive in the pod, on-prem or hybrid by choice, pluggable AI, and a clinician who reviews and signs. Whichever modality a department starts with, it inherits the same way of working, and that does not get diluted as you add more.

Around those products is Myro, an agentic assistant that listens, sees and reasons across the clinical routine — from admin and nursing care to image and lab summaries and the work of a clinical intern — while always leaving the decision to a person. And beyond the clinical platform sits a deliberately free layer: MedPodGP for general practice and Emu for everyone, on-device tools we give away because useful clinical AI should not be gated behind a budget. Together they are one idea, expressed wherever imaging is read and care is delivered.

Platform Myro

Dari pencitraan asli-AI menuju asisten klinis beragen, dan akhirnya menuju AI fisik yang berwujud.

Visi →

AI-native imaging at the point of care Agentic assistant across the workflow Embodied care where it's heading

Berbasis standar, dapat digunakan di lokasi atau hibrida, dan dirancang sesuai standar klinis dan keamanan.

Kepercayaan →

Your facility stays in your control

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