MedPod

TomoPod — An AI-native RIS and PACS for radiology.

TomoEdge gives radiologists desktop tools at their workstation to assist interpretation, with pluggable AI models for the high-compute tasks. TomoPod is a truly AI-native RIS and PACS with semi-automated report generation: AI screens systematically and reduces interpretation time, so the radiologist works as a verifier and approver rather than carrying the whole read alone.

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An AI-native RIS and PACS for radiology.

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public/images/radiology.jpg

Photoreal ~16:11 landscape of a darkened radiology reading room: a radiologist at a multi-monitor diagnostic workstation, screens showing abstract cross-sectional imaging with a soft green (#00BF63) candidate-lesion marker. Cool low ambient light with screen glow, focused verifier mood. Faceless or back three-quarter view; no patient-identifiable data, no real medical-record text, no third-party or competitor logos/UI.

Key capabilities

Desktop tools at the workstation

TomoEdge puts assistive tools right on the radiologist's workstation, fitting the reading desk rather than asking the radiologist to work somewhere new.

Pluggable AI for high-compute tasks

Models plug in for the heavy work and extend over time, so the demanding computational tasks are handled without changing how the radiologist reads.

A truly AI-native RIS + PACS

TomoPod is a Radiology Information System and PACS with assistance built into its foundation — archive, worklist and viewer designed around AI from the start, not bolted on after.

Systematic lesion screening

AI performs systematic screening across the study, surfacing candidate findings consistently so a tired eye at the end of a long list has a steady partner.

The radiologist as verifier

Semi-automated reporting reduces interpretation time and reshapes the role: the radiologist verifies and approves, with a human firmly in the loop, rather than carrying the whole interpretation unaided.

On-prem or hybrid, standards-based

Deploy on-prem or hybrid as you choose, on DICOM and HL7 with a HIPAA-aware posture, so TomoPod fits the modalities and systems you already run.

How it works

Receive into the PACS

Studies arrive into the AI-native RIS and PACS from your modalities as DICOM, on-prem or hybrid by your choice.

Screen systematically

Pluggable AI screens the study for candidate lesions and handles the high-compute tasks before the radiologist sits down to it.

Read at the workstation

With TomoEdge desktop tools, the radiologist reviews the study and the AI-drafted findings together at the reading desk.

Verify, approve & report

A semi-automated report is drafted; the radiologist verifies it, approves or amends, and signs — the human in the loop throughout.

Edge and pod

TomoEdge at the point of care, TomoPod behind it

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

public/images/tomopod-reading.jpg

Photoreal ~16:11 landscape close-up of a radiologist's hands on a reading-room console (mouse, keyboard, dictation device) with diagnostic monitors above showing an abstract imaging series and a green (#00BF63) screening overlay. Cool dim reading-room light, screen glow, precise and unhurried mood. No patient-identifiable data, no real medical-record text, 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

TomoPod 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. TomoEdge 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 TomoPod, 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.

public/images/tomopod-pacs.jpg

Photoreal ~16:11 landscape of an AI-native RIS/PACS worklist on a radiology workstation: a study list and a draft report panel suggested but not legible, with a soft green (#00BF63) status accent indicating AI-screened studies. Cool clinical screen light, organised and efficient mood. 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.

One AI-native RIS and PACS, on-prem or hybrid.

Systematic screening and reduced interpretation time.

The radiologist verifies and approves — always in the loop.

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 models across more modalities, added gradually and customised per department.

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.