MedPod

EndoPod — Real-time endoscopy AI and a complete endoscopic information system.

EndoEdge stands beside the endoscopist during the procedure, offering real-time AI assistance while it captures images and video. Behind it, EndoPod is a full Endoscopic Information System and archive — on-prem or hybrid, standards-based, with a web viewer and AI-assisted reporting that always keeps a human in the loop.

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Real-time endoscopy AI and a complete endoscopic information system.

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public/images/endoscopy.jpg

Photoreal ~16:11 landscape of a modern endoscopy suite: an endoscopist in scrubs working at a procedure tower, looking at a large clinical monitor that shows an abstract endoscopic video frame with a soft green (#00BF63) detection highlight. Cool clinical light, subtle green accents, calm focused mood. Faceless or three-quarter back view; no patient-identifiable data, no real medical-record text, no third-party or competitor logos/UI.

Key capabilities

Real-time assistance at the scope

EndoEdge runs on the endoscopist's device and assists live during the procedure — surfacing what it sees as the examination unfolds, while it captures still images and video clips for the record.

A real Endoscopic Information System

EndoPod is an EIS, not just a viewer: images, videos and patient metadata are organised in a local edge database so a unit can run its endoscopy service end to end.

Standards-based and compliant

Studies are encapsulated as DICOM and the system is built to be HL7- and HIPAA-compliant, so EndoPod fits the wider hospital information landscape rather than standing apart from it.

On-prem or hybrid, in sync

Deploy the pod fully on-prem, or hybrid with a cloud pod alongside it. Edge and cloud stay in sync asynchronously, so a captured study is accessible anywhere it is needed without the edge ever waiting on the network.

Web-based review with AI tools

A web-based viewer brings the study up anywhere, with AI-assisted review tools that help the endoscopist look back over the examination quickly and carefully.

AI-assisted reports, human in the loop

EndoPod drafts the report with AI assistance and a human in the loop — the endoscopist reviews, edits and signs — for a more productive workflow and a better quality of care.

How it works

Assist & capture at the scope

EndoEdge assists the endoscopist in real time during the procedure and captures images and video clips as the examination happens.

Organise in the EIS

Images, video and patient metadata land in the local edge database as DICOM, HL7- and HIPAA-compliant — a complete endoscopic record.

Sync edge and cloud

On-prem or hybrid, the pod keeps edge and cloud in sync asynchronously, so the study is accessible anywhere it is needed.

Review & sign the report

In the web viewer, AI-assisted tools help the endoscopist review the study and draft the report; the clinician edits and signs it off.

Edge and pod

EndoEdge at the point of care, EndoPod behind it

Two layers work together: EndoEdge on the device where care happens, and EndoPod as the information system and archive — on-prem or hybrid, your choice.

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Photoreal ~16:11 landscape close-up of the EndoEdge edge device beside an endoscopy workstation: a compact local appliance and a screen showing an abstract endoscopic-information-system layout — thumbnail captures and a study list, no readable text. Cool clinical light with green (#00BF63) accent edges, shallow depth of field, organised and trustworthy mood. No patient-identifiable data, no real medical-record content, no third-party or competitor logos/UI.

Capture at the edge → sync to the pod → review in the web viewer → sign the report.

Assistive by design — the clinician approves

EndoPod drafts; the clinician decides. The AI proposes findings and a semi-automated report, but a human is always in the loop — reviewing, editing and signing — so the read stays a clinician's read. It is decision support, not a diagnostic device, and that is true at every step.

AI proposes findings; the clinician decides.
Semi-automated reports the clinician edits and signs.
Pluggable AI models, added gradually and customised.
DICOM, HL7 and HIPAA-aware throughout.

How a read flows

From capture at the edge to a signed report

The path from a captured study to a signed report runs through both layers — and a clinician is in command of all of it.

It begins at the device. EndoEdge works beside the clinician where care actually happens, assisting in the moment and capturing the study — images, video or whole-slide images — as the work unfolds. Nothing about the way the department already works has to change for the assistance to be useful; the edge meets the existing instrument rather than asking anyone to adopt a new way of doing the job. The study, and the patient metadata that belongs with it, is organised right there in the local edge database.

From there the study reaches EndoPod, the information system and archive. Encapsulated as DICOM and aligned to HL7 with a HIPAA-aware posture, it sits inside the wider hospital systems rather than apart from them. Whether the pod runs fully on-prem or hybrid — an on-prem pod paired with a cloud pod — edge and cloud stay in sync asynchronously, so the edge never waits on the network and the study becomes accessible wherever it is needed. That is a deployment choice you make, and one you can change as you grow.

The read itself happens in a web-based viewer, with AI-assisted tools and a pluggable, extensible set of models that draft a semi-automated report. Then comes the part that does not move: the clinician reviews what the AI proposed, brings the context the study cannot hold, edits where needed, and signs. The models extend over time and can be customised per customer — turned on for the tasks that help, left off for the rest — but the signature is always a person's. Assistance that could not be reviewed would not be assistance; here it is reviewed, and the report is the clinician's own.

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Photoreal ~16:11 landscape of an endoscopist at a desk reviewing a captured endoscopy study in a web-based viewer on a laptop or monitor: a clip timeline and still captures laid out, a draft report panel suggested but not legible. Cool clinical light, soft green (#00BF63) UI accents, considered review mood. Consented or faceless model; no patient-identifiable data, no real medical-record text, no third-party or competitor logos/UI.

Outcomes

What you can count on from edge to signed report.

Real-time assistance plus a complete endoscopic record.

On-prem or hybrid — your data, accessible anywhere you choose.

AI-assisted reports with the endoscopist signing off.

Why it matters

What changes in the room

Picture a busy session at the end of a long list. Attention is finite, and the hundredth study of the day deserves the same care as the first — but human focus does not naturally cooperate with that wish. AI that screens systematically and quietly flags a region worth a second look does not replace the clinician's eye; it gives that eye a steadier partner, one that does not tire and does not get bored, so the careful read is a little easier to sustain right to the end.

And because the report is drafted for the clinician rather than by the clinician from a blank page, the busywork shrinks while the judgement stays. A semi-automated draft to review is faster than an empty one to fill, a structured result reads cleanly for whoever comes next, and a record encapsulated to standards holds together if anyone ever needs to look back. The clinician still owns the read from capture to signature. The product simply makes that ownership a little less heavy.

Where it's heading

More pluggable AI tasks across the GI workflow, added gradually and customised to each unit.

Frequently asked

On-prem or cloud — which is it?

Whichever you choose. The pod can run fully on-prem, or in a hybrid arrangement where an on-prem pod is paired with a cloud pod and the two stay in sync asynchronously. The edge keeps working through interruptions and reconciles when the link is back. The choice is yours to make and yours to change.

Does it fit a small clinic or a large hospital?

Both. The same architecture flexes from a single small clinic to a medium-to-large hospital — you add capacity and modalities as you grow, without changing the way the system behaves.

Does it fit my existing systems?

It is built on the standards your department already speaks — imaging encapsulated as DICOM, messaging and records aligned to HL7, and a privacy posture designed around HIPAA. That is what lets the pod sit inside the systems you have rather than asking you to replace them.

How does the AI get added?

Gradually. The pod is AI-assisted-ready: models plug in for specific tasks and extend over time, and the set can be customised per customer. You are never forced to adopt everything at once — you turn on what is useful for your work and leave the rest.

Is this a diagnostic device?

No. The AI is assistive and the clinician stays in control — proposing findings, drafting reports and screening systematically, while a person reviews, edits and approves. The intended use is stated for each product.

In the family

Bring clinical AI on-site.