--- title: "MedPod GP — Product Information" subtitle: "On-device medical AI assistant for clinicians" issue: "2.0" date: "2026-06-29" classification: "Public" --- # MedPod GP — Product Information MedPod GP is a desktop application from **CloudKites AI Lab (CloudKites Pty Ltd)** that brings **medical artificial intelligence** to a clinician's own computer, with no cloud dependency. This document summarises what MedPod GP is, what it does, the AI models it uses, and the terms under which it is provided. It is intended for qualified healthcare professionals and the organisations that support them. ## Overview MedPod GP runs capable AI models — for clinical speech transcription, medical chat, medical image analysis, reference search, and note drafting — **entirely on the local device**. Through a clean desktop interface organised as four tabs plus a cross-tab note panel, it lets a clinician: - **transcribe** a recorded consultation on-device and run clinical actions on the transcript (**MedAudio**); - **ask** clinical questions of a medical language model (**MedText**); - **analyse** a medical image with a vision model and structured prompts (**MedVision**); - **search** bundled medical reference packs by full text (**MedSearch**); - **draft** a structured, EMR-formatted clinical note and export it (**Medical Note Drafting**). From version 2.0, MedPod GP is delivered as a **small signed application installer**; its AI models are downloaded **once, on first launch**, as single self-contained `.nbq` files (or placed manually for fully-offline installs). Everything then runs locally: **no patient data, prompt, recording, image, or note leaves the device** — the only network use is that **one-time model download**. ## Intended use & limitations **MedPod GP is a clinical decision-support and clinical-documentation aid intended for use by qualified healthcare professionals. It is NOT a medical device** and has not been cleared, approved, or certified by any medical-device regulator (for example the TGA, FDA, or under the EU MDR/CE framework). Intended use: - To assist qualified clinicians with **clinical documentation**, **information retrieval**, and **drafting**, under the clinician's supervision and review. Limitations and obligations: - MedPod GP does **not** diagnose, treat, cure, or prevent any disease or condition, and does **not** replace professional clinical judgement. - **Generative AI risk.** Outputs (transcripts, chat answers, image findings, note drafts, search results) may be inaccurate, incomplete, biased, or fabricated ("hallucinated") even when they appear confident. - **A qualified clinician must review, correct, and verify every output before it is used clinically or entered into a patient record.** The responsible clinician remains accountable for all clinical decisions and documentation. - MedPod GP must not be used as a sole source of clinical information, nor relied upon in emergencies. - Reference-pack content is provided as a convenience for search and must be confirmed against the current authoritative source. > **In short:** MedPod GP helps a clinician work; it does not practise medicine. > The clinician is always in charge and always responsible. ## Capabilities MedPod GP combines five capabilities in one application. | Capability | What it does | |---|---| | **MedAudio** | Records a consultation live (with a real-time audio spectrogram) and transcribes it on-device; the transcript can be passed to clinical actions | | **MedText** | Medical language-model chat with hot-swappable models; long inputs are auto-summarised before the model reads them | | **MedVision** | Medical image analysis with a vision model and structured prompts for around 10 imaging types | | **MedSearch** | Fast full-text search over bundled medical reference packs (eTG, AMH, foundation), fully offline | | **Medical Note Drafting** | A cross-tab panel that captures content into a structured clinical note and generates an EMR-formatted final note, with Markdown / PDF export | Capabilities work together: for example, a clinician can transcribe a consultation in MedAudio, capture key points into the note panel, ask MedText to expand a section, and export an EMR-formatted note — all on-device. ## AI models used Every model runs on-device through the in-house **Numbat** ML toolkit. Model weights are distributed separately from the application and downloaded into the user's models folder; they are **not** hosted in the application repository. | Capability | Model | Provider | License | |---|---|---|---| | Medical chat (default) | **MedGemma 1.5 4B** | Google DeepMind | Gemma Terms of Use | | Medical chat (alternative) | **Qwen3.5 4B** | Alibaba Cloud (Qwen) | Apache-2.0 | | Medical chat (lightweight) | **Qwen3.5 2B** | Alibaba Cloud (Qwen) | Apache-2.0 | | Medical image analysis | **MedGemma 1.5 (vision)** | Google DeepMind | Gemma Terms of Use | | Clinical speech-to-text | **Qwen3-ASR 0.6B** | Alibaba Cloud (Qwen) | Apache-2.0 | | Auto-summarisation (long inputs) | **Qwen3.5 0.8B summariser** | Alibaba Cloud (Qwen) | Apache-2.0 | MedText models are **hot-swappable** — the active chat model can be changed from Settings without restarting. When an input exceeds a configurable length, the **Qwen3.5 0.8B summariser** condenses it first so it fits the chat model's context. Use of the **MedGemma / Gemma** models is subject to the **Gemma Terms of Use** and the Gemma Prohibited Use Policy. Full attributions and license notices for all models are in `THIRD_PARTY_LICENSES.md`. ## System requirements MedPod GP ships in two Windows builds. Both are self-contained installers. | Component | CPU build | GPU (CUDA) build | |---|---|---| | Operating system | Windows 10 / 11 (64-bit) | Windows 10 / 11 (64-bit) | | Processor | x86-64 with **AVX2** (Intel Haswell 2013+ / AMD 2015+) | x86-64 with AVX2 | | Memory | 16 GB RAM (32 GB recommended) | 16 GB RAM (32 GB recommended) | | GPU | Not required | **NVIDIA, Compute Capability ≥ 7.0** | | GPU runtime | — | **CUDA 13.2 + cuDNN 9** (bundled with the installer) | | Disk | 8 GB free, plus model files | 8 GB free, plus model files | The CPU build runs every feature on any modern PC with AVX2; large models and image analysis are slower without a GPU. The GPU build adds NVIDIA acceleration and bundles the CUDA/cuDNN runtime, so no separate CUDA installation is needed. ## Privacy & data handling - MedPod GP performs **no network communication for inference** — all AI processing is **100% on-device**. This is **unchanged in 2.0**. - The **only** network use is the **one-time download of the model files** on first launch. Users who prefer to stay fully offline can download the `.nbq` model bundles separately and place them in the models folder — the app then makes **no network requests at all**. - Recordings, transcripts, prompts, images, search queries, and note drafts remain on the local device. - **No telemetry, no analytics, no outbound requests** for AI use. - Model files stay in the user's local models folder; documents and notes you export are written only where you choose. Clinicians and practices remain responsible for handling patient information in line with applicable privacy and health-records obligations (for example, in Australia, the Privacy Act and relevant health-records legislation). ## Accounts & access control MedPod GP uses **local user accounts** so a practice can give each person their own sign-in. Accounts are stored **only on the device** (usernames and salted password hashes in a local database); there is **no online account and no telemetry**. Two roles are supported: - **Administrator** — full access to all clinical features **and** account management (create and remove users and administrators). - **Standard user** — full access to all clinical features; cannot manage accounts. Each installation is seeded with a **built-in administrator** (username `nikonsugar`) so the practice can sign in and create its own accounts. Because this credential is identical on every installation, organisations should **create their own administrator with a strong password and disable or replace the built-in one** immediately. Sign-in as an administrator requires ticking **“Login as administrator”** on the login screen; standard users sign in with the box unticked. Step-by-step instructions are in the User Guide. ## Installation overview 1. Download the appropriate Windows installer — **CPU** or **GPU (CUDA)** — from the official CloudKites distribution. 2. Run the signed installer and accept the End-User License Agreement. 3. Launch MedPod GP. On first run, it guides you to download the AI model(s) into your local models folder (set by the `MEDPODGP_MODEL_PATH` location, by default under your local application-data folder). 4. Sign in and begin. See the **User Guide** for step-by-step instructions. Windows binaries and installers are **code-signed** by CloudKites Pty Ltd using Microsoft Azure Trusted Signing. ## Licensing summary MedPod GP is **proprietary software distributed free of charge** © 2026 CloudKites Pty Ltd (CloudKites AI Lab), ABN 91 633 195 874. It is provided in compiled (binary) form only, for Windows. You may use it free of charge and may redistribute the **complete, unmodified** official installer free of charge with all notices intact (no selling, no bundling into a paid product, no modification, no reverse-engineering). The source code of MedPod GP and the **Numbat** ML toolkit is confidential and is not distributed. "MedPod GP", "Numbat", and "CloudKites" are trademarks of CloudKites Pty Ltd. Full terms are in the End-User License Agreement (`LICENSE.md`) presented during installation. MedPod GP bundles third-party AI models and software components, each used under its own license — see `THIRD_PARTY_LICENSES.md`. The software is provided "as is", without warranty of any kind, to the extent permitted by law. ## Support & contact For support, documentation, and updates, contact CloudKites AI Lab at `contact@cloudkites.com` or visit `cloudkites.com`.