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An idea arrives while you are between tasks. You can say it in ten seconds, but opening a planner and sorting it into fields interrupts the thought. OGAD (Off Grid AI Desktop) Pro can turn a short dictated note into suggested to-dos. Enable **Feed to memory** in Voice, record the note, and local models can extract the next steps. You still choose when recording starts and review what the AI saved. Download OGAD for Mac | Beta 0.0.52-beta.103 ## Give a spoken idea a place to go Say the action and enough context to recognize it later: > For the workshop, draft three exercises and send the outline to Maya for review. After transcription, OGAD can identify people, projects and actions from the note. The result can appear in the Voice record and the **Actions** to-do list. This is useful for a plan after a call, a task remembered during a walk around the room, or a short end-of-day note. The extraction is a draft. It can miss an action or split one thought into several items. Short notes work better for review than a long, unstructured monologue; this route does not process an unlimited transcript in one pass. ## Prepare local speech and text models Use OGAD Pro on a supported Mac. This guide follows the linked beta. In **Voice → Voice settings → Transcription** , prepare a downloaded local speech model. In **Models → Text** , select a downloaded local text model for the separate extraction step. Speech recognition produces the words. The text model finds actions in those words. Both choices must be local for the complete workflow to remain local after setup. Allow microphone access. The global shortcut can also need Accessibility permission. Internet can be needed for installation, licence setup and model downloads. ## Record your first task note 1. Open **Voice settings** and turn **Feed to memory** on. 2. Turn **Paste at cursor** off if you only want to save a note. Leave **Auto-send** off. 3. Choose **Toggle** under **Activation → Mode** for a recording you start and stop with the shortcut. 4. Press your configured shortcut, normally **Option+Space** , and wait for the visible recording indicator. 5. Speak one or two concrete actions. Press the shortcut again to stop. 6. Wait for transcription and background processing, then inspect the Voice record and **Actions → To do**. Turning on Feed to memory does not start ambient listening. Each note still needs a recording that you start. Turning it off stops this destination for future dictation; it does not erase previously extracted records. ## Review the task before you depend on it Compare the suggested action with the saved transcript. Check names, dates and whether the wording actually commits you to do something. If the model missed an item, use **Jot a to-do** in Actions. If it invented a task from a general thought, dismiss it. Do not assume a spoken deadline was converted into a correctly scheduled reminder. A note saved in Voice does not guarantee that extraction succeeded. If no task appears, check the transcript first, then the local text model. You can use the transcript to add the missing action yourself without recording it again. ## Choose what you retain Voice history and the memory-derived to-dos are separate records. Deleting the recording should not be treated as deleting every extracted task or observation. Review both places when you want to remove the result. Try OGAD for Mac, enable Feed to memory, and record one short plan. Check the extracted actions before using this route for your next real task.

You can ask questions about saved voice notes without uploading them to a cloud AI service. OGAD (Off Grid AI Desktop) transcribes audio imported into a project, searches the resulting text, and uses relevant passages to answer your question. Download the required models first, then keep the speech and chat models local. Download OGAD | Desktop features and releases This guide uses the free desktop core on an Apple Silicon Mac or Windows x64 PC. It covers saved audio files that you add to a project yourself. For example, you might have separate voice notes about a repair, a delivery, and a meeting. Instead of remembering the filename, ask, "What did I say about the delivery date?" The app retrieves relevant transcript passages and gives them to your local chat model. ## What makes this an AI search workflow? The project search compares your question with indexed transcript passages, then a chat model generates an answer from the retrieved material. You can ask a question instead of typing an exact phrase. The answer should name the source file so you can check it against the original recording. There are separate local steps: Step | What it does | What you need ---|---|--- Transcription | Converts the audio into text | A downloaded local speech model Indexing and retrieval | Finds transcript passages related to your question | The app's local search model Answer generation | Uses those passages to answer | A downloaded local chat model The search model can need a download on first use. Complete your first import and test question while connected before you test the full workflow offline. OGAD Pro also has a Voice library with a **Search transcripts** box. That box performs text matching. This guide uses project chat for questions and generated answers. ## What do you need before you start? Install the current desktop app and save your voice notes as local audio files. Use MP3, WAV, or M4A for a first test. You need enough disk space for the models and indexed text, plus enough available memory to run the models you select. Prepare these items: * A downloaded local transcription model, such as multilingual **Whisper Base**. * A downloaded local text model that fits your computer. * Two short voice notes whose contents you know. * Internet access for app and model setup, including the initial search-model download. Whisper Base is about **148 MB** in the desktop catalog. Whisper Small is about **488 MB** if you want to compare recognition later. These are approximate download sizes, not total RAM requirements. The free desktop feature list includes Projects, audio uploads, and chat grounded in project sources. You do not need Pro for this workflow. ## How do you prepare the local models? In **Models > Transcription**, download a multilingual speech model and select **Use**. In **Settings > Transcription**, confirm **Current model** and set **Spoken language** for your recordings. Then download and activate a local text model in **Models > Text** for the answers. For English-only notes, either an English-only or multilingual speech model can be appropriate. For French, Hindi, or another supported language, choose a multilingual model. A filename containing `.en` identifies an English-only Whisper model. Use the language you actually recorded. Do not expect an English-only model to become multilingual when you change your computer's language. Check the active chat model separately. A local speech model can produce transcripts even while your selected chat model depends on a remote server. Both must be local for the workflow described here. ## How do you add voice notes to a searchable project? Create a project, open **Knowledge & settings**, and choose **Add files** under **Knowledge base**. Select the saved audio files and wait for indexing to finish. The project stores extracted text for retrieval. You then start a chat from that project so the question uses its knowledge base. ### 1. Create a small test project Open **Projects** and select **New project**. Enter a name such as "Voice notes test" and press Enter. For the first test, use two short recordings with different topics. Give the files useful names, such as `delivery-note.m4a` and `repair-note.m4a`. Those names help you identify sources in an answer. ### 2. Import the recordings Open **Knowledge & settings** for the project. Under **Knowledge base** , select **Add files** and choose your audio files. Wait while the app extracts, processes, and indexes the text. A completed progress message shows the filename followed by **indexed**. Check that each file is in the knowledge-base list and enabled for retrieval. Keep your originals. The project index is a way to search extracted information, and you will still need the recordings to check recognition errors. ### 3. Start a project chat Select **Chats** , then **New chat** within that project. The conversation opens in the main Chat screen with the project attached. Do not start an unrelated chat and expect it to use these files. The project links the question to the uploaded notes. ### 4. Ask a question you can verify Try: > According to my uploaded voice notes, what delivery date did I mention? Name the source file. If the notes do not contain a date, say so. Compare the answer with your recording. A useful first result names the relevant file and preserves the detail you asked about. The model is instructed to cite source filenames. It can still make mistakes. Asking it to say when information is missing helps state your intent, but does not guarantee that every answer follows the instruction. ### 5. Test without internet After the first import and answer work, turn off Wi-Fi and disconnect Ethernet. Ask a different question about the same project. For example: > What did I say needed to happen before the delivery? Use only the project notes and name the source. This checks the local search and local answer path with the models already available. If it fails, check which step still needs setup before importing more notes. ## How do you check the sources behind an answer? Read the source filename in the response and open the source-information disclosure when it is available. Project answers carry the retrieved source names and passage positions. Use that information to identify the recording you need to verify. The current interface can label this disclosure **Searched your memory** even for project results. For this workflow, the underlying sources are your enabled project files. A source reference shows which material was retrieved. It does not prove that every statement in the generated answer is correct. Replay the original when checking a person's name, an amount, or a deadline. Keep questions specific. "What date did I mention for the delivery?" gives the system a smaller task than "Tell me everything important in every recording." ## What are the limits of searching voice notes this way? The app searches transcript text, so recognition errors affect retrieval. If a name is transcribed incorrectly, the answer may miss that note or repeat the wrong name. Use clear recordings, check important details, and compare another speech model when transcription quality is poor. Each answer uses a limited set of retrieved passages. It does not read every word of every recording for every question. A broad request for every commitment across hundreds of notes can miss items. Project chat can also use recent conversations from the same project. Keep a dedicated project for the notes you want to search, and ask for the uploaded-file source when you need to distinguish recorded facts from earlier discussion. This procedure does not automatically scan your phone's voice recorder, every folder on your computer, or your Pro Voice history. Add the audio files you want the project to use. ## What should you check if the offline answer fails? Problem | Check | Action ---|---|--- The audio import fails | Local transcription model and audio format | Select a downloaded speech model and try a short MP3, WAV, or M4A file. Indexing fails after transcription | Initial search-model download | Reconnect to finish setup, then import a test note and ask a question before disconnecting again. The answer ignores a file | Project selection and file status | Open the chat from the correct project and ensure the file is indexed and enabled. An offline transcript works, but the AI reply does not | Active text model | Select a downloaded local text model. The answer misses a name | Speech recognition or retrieval | Try a topic or nearby detail from the recording. Check the original and consider importing corrected transcript text. The answer combines unrelated information | Project contents and earlier chats | Use a smaller project and ask for a specific uploaded source. The answer claims something absent from the notes | Model error | Ask for the supporting source, then verify it. Do not treat an unsupported answer as a fact. ## Where do the recordings and transcripts go? With a local transcription model selected, the speech is processed on your computer. Project indexing stores extracted text and search data locally. The local chat model then receives retrieved passages to generate the answer. Initial model downloads still require a connection. Remote speech or chat selections change where content is processed. Device sync or external tools are separate features; keep them outside this test if you want to check a single-device offline workflow. ## Voice-note search FAQ ### Can I use this without Pro? Yes. The desktop project workflow uses uploaded audio and local models in the free core. Pro's recording library and captured-memory features are separate. ### Can the AI search without the exact words I said? Project retrieval compares your question with transcript passages. It can find related text without an exact phrase match, but a result is not guaranteed. Names, short fragments, and poor transcripts can be difficult to retrieve. ### Can I add a corrected transcript instead of the audio? Yes. Projects accept text files. Save the corrected transcript as a local text or Markdown file and add it to the knowledge base. Disable the incorrect source if you do not want both versions used. ### Does a citation mean the answer is accurate? No. Check the cited source and the original recording. Retrieval and answer generation are separate steps, and either can produce an error. Start with two short voice notes. Ask one question whose answer you already know, check the source, then repeat with the internet disconnected.

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