medpodgp

MedPod GP — On-Device Medical AI Assistant

MedPod GP is a desktop medical AI assistant for clinicians and general practitioners that runs entirely on your own computer. Dictate and transcribe clinical encounters, chat with a medical language model, analyse medical images, search trusted reference packs, and draft structured EMR-ready notes — all on-device, with no cloud account, no telemetry, and no network calls for inference.

A product of CloudKites AI Lab (CloudKites Pty Ltd), Sydney, Australia.

💚 Free to download, use, and share. MedPod GP is distributed free of charge. You may use it and redistribute the complete, unmodified official installer for free (no selling, no paid bundling). See License below.

⚕️ Clinical decision-support / documentation aid — not a medical device. MedPod GP does not diagnose, treat, or replace professional medical judgement. All AI output must be reviewed and verified by a qualified clinician. See the Medical disclaimer & intended use section below.

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⬇️ Installation (Windows) — v2.0

New in 2.0: one small app installer, models on first run. You install a single code-signed app (~80 MB). The first time you launch it, MedPod GP downloads its AI models — now packaged as single self-contained .nbq files — straight into your local models folder, with a progress screen. After that, nothing is downloaded again and everything runs on-device.

🔒 Offline & privacy — unchanged. MedPod GP still runs 100% on your computer: no cloud account, no telemetry, and no network calls for any AI inference. The only time it uses the internet is to download the model files once (or when you add a feature). Prefer to stay fully offline? Download the .nbq files manually (table below) and drop them into your models folder — the app finds them and never touches the network. See “Fully offline / manual install” below.

Step 1 — Install the MedPod GP app

Download one build and run the installer (code-signed, Microsoft Azure Trusted Signing):

Optimized CPU builds (advanced). Faster prompt processing / image analysis on newer CPUs. Each requires the matching CPU feature and won't run otherwise — if unsure, use the standard CPU build (it runs everywhere).

GPU (CUDA) build. Have a supported NVIDIA card? Use the CUDA build for the fastest transcription, chat, and image analysis. It bundles the CUDA + cuDNN runtime — nothing extra to install.

Step 2 — First launch downloads the models

Launch MedPod GP. If the model files aren't present yet, it shows a first-time setup screen that downloads the bundles it needs and shows progress. When it finishes, sign in and start working — no further downloads, ever. A download that gets interrupted resumes where it left off when you retry.

Fully offline / manual install

You can skip the in-app download entirely: grab the .nbq files below and place them in your models folder — %LOCALAPPDATA%\medpodgp\models (e.g. C:\Users\<you>\AppData\Local\medpodgp\models). The app detects them on launch and runs without any network access.

Match the bundles to your build. Two of the models (text, summariser) are device-neutral — the same file works on the CPU and CUDA builds. The other two (vision, ASR) ship device-specific weights, so a CPU build uses the -cpu bundle and a CUDA build uses the -cuda bundle. Download the two shared files plus the two that match your build.

Shared by both builds:

CPU build only:

CUDA (GPU) build only:

Each .nbq is a single self-contained, integrity-checked file holding the model's (unchanged, same-quality) weights plus its tokenizer/config — so the app loads one file and is ready. The first-run downloader automatically fetches the right set for your build; the table above is only for manual/offline placement. MedSearch reference search needs no model.

Signing in & accounts

MedPod GP has local user accounts (stored only on your PC — no online account, no telemetry). There are administrators (can use every feature and manage accounts) and standard users (every clinical feature, no account management).

First sign-in — built-in administrator:

On the login screen, enter these, tick “Login as administrator,” and click Sign in. 🔐 Change this right away — it's the same on every install, so it isn't secret. Create your own admin with a strong password and use that instead.

• Create a user: signed in as an admin, open the administrator dashboard → Accounts, click Add User, set a username + password (+ optional display name), Save. (Use Add Admin to grant another person admin rights.)
• Log out / switch user: click Logout in the top bar; sign in as the other user — leave “Login as administrator” unticked for a standard account.

Full step-by-step instructions are in the User Guide below.

Documentation: User Guide (PDF) · Product Information (PDF) · License

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✨ Features

MedPod GP combines five clinical capabilities in one private, offline workspace:

• 🎤 MedAudio — clinical transcription. Record a consultation live (with a real-time audio spectrogram) and transcribe it on-device with Qwen3-ASR 0.6B, then run clinical actions on the transcript.

• 💬 MedText — medical chat. Ask clinical questions of a hot-swappable medical language model: MedGemma 1.5 4B, Qwen3.5 4B, or Qwen3.5 2B. Long inputs are auto-summarised before the model reads them.

• 🩻 MedVision — medical image analysis. Upload a medical image and analyse it with the MedGemma 1.5 vision pipeline, with structured prompts for around 10 imaging types.

• 🔎 MedSearch — reference search. Fast full-text search over bundled medical reference packs (eTG, AMH, foundation) — answers in milliseconds, fully offline.

• 📝 Medical Note Drafting. A cross-tab panel that captures content from any tab into a structured clinical note and generates an EMR-formatted final note, with Markdown / PDF export.

• 100% private & offline. Every model runs on your CPU or NVIDIA GPU; nothing leaves your device. No account, no telemetry.

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💻 Which build for my computer?

If you are unsure whether your processor supports AVX2, the CPU build runs on essentially every Windows PC built since about 2014. Choose the GPU (CUDA) build whenever you have a supported NVIDIA graphics card.

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⚡ Expected performance (rough guide)

AI speed is described by two numbers, both in tokens per second (tok/s):

• Decode — how fast a reply or transcript is generated. This is limited by your RAM speed (or GPU memory), not by the CPU model — so faster RAM, and dual-channel (two sticks) instead of single-channel, matters most.
• Prefill / prompt — how fast a prompt (or image) is read in before the reply starts. This is limited by CPU compute, so more cores and the optimized AVX-VNNI / AVX-512 builds help here.

Rough estimates for the two main models — MedGemma 1.5 4B (chat / vision) and Qwen3-ASR 0.6B (transcription), both 4-bit. Treat as ballpark (±~30 %); MedPod GP shows live tok/s so you can see your real numbers.

Notes

• Single-channel RAM ≈ half the decode speed of the figures above — use two matched sticks for dual-channel.
• The optimized Raptor Lake / AVX-512 builds mainly speed up prefill and MedVision image analysis (compute-bound); decode is RAM-bound, so the gain there over the standard CPU build is small.
• 16 GB RAM comfortably runs chat + transcription. MedVision, very long chats, or heavy multitasking need more — if RAM runs out the PC pages to disk and everything slows sharply (32 GB is safer for those).

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⚕️ Medical disclaimer & intended use

MedPod GP is a clinical decision-support and documentation aid intended for use by qualified healthcare professionals. It is NOT a medical device and has not been cleared or approved by any medical-device regulator (e.g. TGA, FDA, CE/MDR).

• It does not diagnose, treat, cure, or prevent any disease or condition.
• It does not replace the clinical judgement of a qualified clinician.
• All AI-generated output — transcripts, chat responses, image findings, note drafts, and search results — must be reviewed, corrected, and verified by a qualified clinician before any clinical use or entry into a patient record.
• The responsible clinician remains accountable for all clinical decisions and documentation.
• Do not rely on MedPod GP in emergencies or as a sole source of clinical information.

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📜 License

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 for Windows.

• ✅ Free to use — for qualified clinicians and healthcare settings, on any number of devices.
• ✅ Free to redistribute — you may share the complete, unmodified official installer, free of charge, with all notices intact.
• ❌ No selling / no paid bundling, no modification, no reverse-engineering.
• The source code of MedPod GP and its Numbat ML toolkit is confidential and is not distributed.

Full terms: LICENSE.md. "MedPod GP", "Numbat", and "CloudKites" are trademarks of CloudKites Pty Ltd.

Bundled AI models remain under their own licenses — see THIRD_PARTY_LICENSES.md. Use of the MedGemma / Gemma models is additionally subject to the Gemma Terms of Use and Prohibited Use Policy.

Note on models. The AI models are provided as separate code-signed Windows model installers on this page (see Installation → Step 2). Each bundled model remains under its own license — use of the MedGemma / Gemma models is subject to the Gemma Terms of Use and Prohibited Use Policy.

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⚠️ AI output notice

MedPod GP uses generative AI models. Output may be inaccurate, incomplete, or fabricated ("hallucinated") even when it appears confident, and is not a substitute for professional clinical judgement. A qualified clinician must verify every output before use.

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Contact: contact@cloudkites.com · cloudkites.com