# How to Turn Internal Documents Into a Public-Facing Draft With Local AI in 2026 > Source: > Published: 2026-09-29 14:05:41+00:00 An internal document often contains the clearest explanation of your work, along with details that should stay internal. OGAD (Off Grid AI Desktop) can help turn approved material into a public-facing draft on your computer. A local model lets you work without uploading the source to a cloud AI service. You decide which facts are cleared for publication before asking for the final copy. [Download OGAD](https://getoffgridai.co/desktop/) | [Desktop releases](https://github.com/off-grid-ai/OGAD/releases) **What would you like to do with Off Grid AI?** Have a feature or use case you would like us to support? Tell us what you want to do and which device you use. Write to [support@offgridmobileai.co](mailto:support@offgridmobileai.co), [join our Slack community](https://join.slack.com/t/off-grid-mobile/shared_invite/zt-3swt3s84k-R0CHRwISaUpExV2~3qUUdQ), or [talk to us on Reddit](https://www.reddit.com/r/off_grid_ai/). Choose the output first: a website page, a help article, a project story, or a product announcement. Then define the audience and the facts they need. Suppose a small software team has an internal launch note. It describes a useful feature, an unresolved bug, a customer incident, and an unannounced roadmap. A public help article may need only the feature's supported workflow and limits. Rewriting the whole note in a friendly tone could expose the other details. The useful first step is therefore selecting publishable evidence. Polished prose comes later. Create a short working document with three sections: | Section | What belongs there | |---|---| | Approved facts | Details you can support and are permitted to publish | | Required limits | Conditions readers need to use the information correctly | | Excluded material | Topics or identifiers that must not appear | A limit is not automatically confidential. If a feature requires a specific device or a manual step, the reader may need that information. Keep honest constraints in the public explanation while removing unrelated internal discussion. Do not use the model to decide whether a customer name or result is approved. Get that decision from the person responsible. An internal statement that a launch “went well” is not evidence for a public numerical claim. Install the desktop app and download a local text model that fits your computer. Complete the initial model and search setup while connected. Projects and document chat are core features; recording your activity is not required. For a short fact sheet, you can paste it into a new chat. For several documents, use **Projects > New project**, then **Knowledge & settings > Knowledge base > Add files**. Add text-based PDF, DOCX, TXT, or Markdown sources, wait for indexing, and start **Chats > New chat** inside the project. If you use Pro, disable **Include captured memory** for a source-only writing project and save. Keep remote models and external tools out of this local-only workflow. Device sync has separate behavior, so use only the destinations you intend. The [Projects implementation](https://github.com/off-grid-ai/OGAD/blob/v0.0.51/src/renderer/src/components/ProjectsScreen.tsx) supports file selection and project instructions. It does not make a project a public-content approval system. Give the model a clear reader task: Create an outline for a public help article using only the approved fact sheet below. The reader wants to complete the stated task. Include the result, requirements, steps, and limits. Exclude the listed internal topics. Flag missing information instead of inventing an answer. Read the outline and ask whether it serves the reader. Internal headings such as “Phase two dependency” may need to become a practical question such as “What do I need before starting?” For the fictional software example, the outline could explain a file-import workflow, supported input types, and what to check when an import fails. It should not mention the customer incident just because that incident helped the team write the internal note. Once the outline is useful, ask: Write the article from this outline and approved fact sheet. Use plain language and concrete steps. Do not add customer names, performance figures, endorsements, or future plans. Where a step lacks enough detail, insert a visible question for the editor. Keep required limitations next to the claims they qualify. For important sentences, request a separate claim table. Ask the model to list each factual claim and the source passage that supports it. This table is for your review; it does not need to appear in the public article. Check the draft against the fact sheet. If the model writes “works with any file,” but your source lists only three formats, correct the claim rather than asking for a more persuasive version. You may use local AI to help inspect a broader internal source, but the final draft should use the approved fact sheet. This gives you a smaller set of material to verify. For stronger separation, create a new project containing only the approved facts. Earlier conversations in the same project can provide context, so removing a file alone is not the same as starting with a clean writing context. This is an editorial control, not certified data isolation. It helps you avoid accidental carry-over while keeping the writing process understandable. Review the draft for these common problems: | Claim type | Check before publication | |---|---| | Capability | Is it released and available to the stated reader? | | Result | Was it actually measured, and can it be published? | | Customer example | Is permission clear, including names and quotes? | | Future statement | Has the team approved that commitment? | Also check that descriptive words have support. “Automatic” may be wrong if a person must start each run. “Offline” may be wrong if one step calls an online service. A small wording change can create a large promise. For long sources, retrieval may omit relevant passages. Review requirements and limitations directly rather than assuming the model has seen every appendix. Copy the checked text into your publishing tool. Inspect titles, captions, links, filenames, image text, and document metadata separately. If you reuse an internal screenshot, check it for names, account details, and private material. Have the appropriate owner review the content before publication. OGAD can draft and organise evidence, but it does not decide who has authority to release company information. Keep the approved fact sheet and final text together so later changes can be checked against the same basis. That makes the next update easier than reconstructing why each claim appeared. [Download OGAD](https://getoffgridai.co/desktop/) and choose one question customers ask. Build a short approved fact sheet and turn it into a useful answer. The aim is a draft that helps the reader and that your team can support sentence by sentence.