Dot
A free desktop app that runs the Mistral 7B model on your own machine, so you can chat with spreadsheets and PDFs without uploading them anywhere.
Pick Dot when the file itself is the sensitive part — contracts, research data, internal spreadsheets — and you'd rather run the model than sign a DPA. It is free, it runs the Mistral 7B LLM locally, it works offline after the model download, and the document-plus-Big Dot split covers most individual needs. Pass if you need shared workspaces, web-connected answers, or zero-install convenience; cloud document AI like NotebookLM or ChatGPT file uploads is a different product with a different data path.
Verified 2d ago · liveness 66/100 · cite: rightaichoice.com/tools/dot
- Solo users who cannot upload files to a cloud service
- Researchers and engineers querying local spreadsheets, specs or PDFs
- Anyone working without reliable internet who still wants an LLM on hand
- Hobbyists who want a free, no-account way to draft emails or code from their own data
- Teams that need shared document workspaces or multi-user collaboration
- Buyers who want zero-install, browser-based AI assistance
- Workflows that depend on web browsing, live search or third-party app integrations
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Skip Dot if you need one shared workspace across a team, or answers that require live web information — both are outside what a locally-run document model can give you.
Dot itself is free, but you pay in hardware: the machine has to be capable of running the Mistral 7B LLM locally, which is a real cost if your current laptop struggles.
At $0 the beta sits below every paid cloud document-AI tier you'd compare it to — the trade is that you fund the compute instead of a subscription. It suits a solo user or a small consultancy with one decent desktop machine; teams that need seats, shared workspaces and admin controls should budget for a cloud tool with per-seat pricing rather than trying to make a free local app cover group workflow.
In short
Dot — A free desktop app that runs the Mistral 7B model on your own machine, so you can chat with spreadsheets and PDFs without uploading them anywhere. Best for Solo users who cannot upload files to a cloud service, Researchers and engineers querying local spreadsheets, specs or PDFs, Anyone working without reliable internet who still wants an LLM on hand. Free to use.
What people actually say about Dot — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
107 mentions across 7 sources (Hacker News, YouTube, Product Hunt, App Store, Bluesky, Stack Overflow, Lemmy) · researched Jul 14, 2026.
Average across the 7 sources that answered — each source counts once, not each post.
- +Full privacy – documents never leave your device.
- +Works entirely offline after initial model download.
- +Supports document uploads like PDFs and spreadsheets.
- +Simple chat interface for document Q&A.
- +Free to use – no subscription fees.
- −Only one model (Mistral 7B) – no model choice.
- −No cloud/web version – local installation required.
- −Limited to desktop – no mobile app support.
- −Community support is scarce and hard to find.
- −Beta software – bugs and incomplete features expected.
- • Requires a capable machine (GPU recommended) which is a hardware cost
Viability Score
How well maintained and how widely used is Dot? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- Local document chat powered by the Mistral 7B LLM
- Runs entirely on your own device with no data sent to the cloud
- Works offline after the initial model download
- Upload spreadsheets and PDFs and query them in natural language
- Extract table rows, prices and dimensions from uploaded files
- Draft emails and replies grounded in uploaded document content
- Big Dot mode for general chat with the latest Mistral model
- Generate Python code, including matplotlib plots from CSV data
- Generate everyday content such as recipes in Big Dot mode
- Follow-up questions that keep context across a document session
- Desktop app for macOS, Windows and Linux
- Beta build distributed via GitHub
- No cloud account or API key required
About Dot
Dot is a free desktop app for macOS, Windows and Linux that runs the Mistral 7B language model on your own hardware. You upload your own spreadsheets and PDFs and ask questions in plain English — the vendor's homepage demo pulls line-item prices out of a rocket-parts spreadsheet (a Drogue Parachute at £136.44, a VEGA flight computer at £307, a DJI drone at £439), reports the rocket's dimensions (306cm long, 10.2cm outside diameter), and then drafts a follow-up email to the colleague named in the file, Mr. Pinel, who is working on the nose cone. Two modes handle the work: a document mode that keeps answers grounded in the files you uploaded, and Big Dot, a general chat mode for anything unrelated to your documents — chicken recipes, Python code, a matplotlib plot from a CSV. Because the model runs locally, Dot keeps working offline after the initial download and needs no cloud account or API key. The beta is distributed through GitHub. That privacy costs you cloud conveniences: there are no shared workspaces, no web-connected answers, and you supply the hardware capable of running the model. For a solo user who will not hand sensitive files to a vendor, that is the trade.
Behind the Verdict
Dot's whole argument is that the data path is the product. Everything the vendor shows on the homepage is grounded in that: the demo sheet with real line items and pound prices, the follow-up email addressed to the colleague named in the file, the dimensions answer pulled from the rocket spec. None of it requires a server. You download the app, it runs the Mistral 7B LLM on your machine, and after the initial model download you can keep working with the Wi-Fi off. The two-mode design is the part worth understanding before you install. Document mode keeps the conversation tethered to what you uploaded — ask what the spreadsheet components cost and you get the component rows, not an invented answer. Big Dot drops the tether and hands you the general Mistral model for recipes, Python snippets, or a matplotlib plot built from a CSV. That split is sensible: it stops a casual question from being answered out of your confidential files, and it stops your file questions from drifting into general knowledge. Strengths: no account, no API key, no data transfer; desktop builds for macOS, Windows and Linux; offline operation; and a genuinely free beta distributed through GitHub. For audit, research or engineering work on documents you cannot ship to a third party, that combination is hard to match at any price, let alone zero. Where it does not fit: teams. There are no shared workspaces and no multi-user collaboration, so a group that needs one canonical answer across five people is looking at the wrong shape of tool. It is also desktop-only with a hardware requirement — you are the one supplying the compute that a cloud service would otherwise supply. And there is no web browsing or live search in the loop, so anything that depends on current information outside your files is out of scope. One caveat specific to this page: the vendor's site surfaces the beta, the Mistral 7B model and the GitHub download, but it does not publish dated changelog, release-note or blog entries we could verify this run, so we have no dated release history to report. Treat the beta as a beta. Who it is for: the solo researcher, engineer or consultant whose blocker is the file, not the model. If your blocker is collaboration or convenience, pay for a cloud tool and get a DPA.
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Real-world workflow fit
Concrete scenarios for the personas Dot actually fits — and what changes day-one when you adopt it.
You receive a supplier spreadsheet of rocket parts and a PDF spec, and your client forbids uploading either to a third party. You install Dot, let the Mistral 7B model download, load both files into document mode, and ask what the components cost and what the rocket's dimensions are.
Outcome: You get the line items with prices and the 306cm length and 10.2cm outside diameter back without anything leaving your machine, then ask Dot to draft the follow-up email to the engineer named in the file.
You are on a site or a locked-down network with no dependable connection. You ask Dot document-mode questions about the internal PDFs you brought with you, then switch to Big Dot for a Python snippet that plots a CSV you already have on disk.
Outcome: Both the document answers and the code generation work offline after the initial download, with no account login and no API key to configure.
You don't have sensitive files, you just don't want another subscription. You install the GitHub beta, use Big Dot for a recipe or a bit of brainstorming, and keep document mode for the occasional spreadsheet question.
Outcome: A working local LLM on your desktop at no cost, with the caveat that everything runs on the hardware you already own.
Use Cases
- Chat with your spreadsheets to pull specific line-item prices or summaries.
- Ask questions about PDF documents without uploading them to a cloud service.
- Draft a follow-up email grounded in the details of an uploaded project file.
- Use Big Dot for casual conversation or brainstorming while offline.
- Interrogate internal documents for research or audit purposes on a disconnected machine.
- Generate Python code and matplotlib plots from a local CSV.
- Run a local AI assistant for note-taking or task planning with no internet.
Models Under the Hood
as of 2026-10-18
Limitations
- Dot runs the Mistral 7B LLM locally on your device, so documents and data never leave the machine, and it keeps working offline after the initial model download.
- It is currently in beta, with the build distributed via GitHub and desktop downloads for macOS, Windows and Linux.
- You supply the hardware capable of running the model, and the app is desktop-only.
- Functionality centres on uploading and chatting with your own documents plus general text generation in Big Dot mode.
- There are no shared workspaces, no multi-user collaboration and no web browsing or live search inside the app.
as of 2026-10-10
Verification history
We have re-verified Dot 8 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-checked, vendor evidence unchanged
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 8 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Dot tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Free (Beta)
$0
Ideal for
Solo users, researchers and hobbyists who need document Q&A on a machine that can run a 7B model and cannot send files to a cloud service.
What this tier adds
Starting tier — everything Dot does is included at $0: local Mistral 7B, document mode, Big Dot mode, offline operation and desktop builds for macOS, Windows and Linux.
Where the pricing makes sense
The company stage and team size where Dot's pricing actually pencils out — and where peers do it cheaper.
At $0 the beta sits below every paid cloud document-AI tier you'd compare it to — the trade is that you fund the compute instead of a subscription. It suits a solo user or a small consultancy with one decent desktop machine; teams that need seats, shared workspaces and admin controls should budget for a cloud tool with per-seat pricing rather than trying to make a free local app cover group workflow.
Setup time & first value
How long it actually takes to get something useful out of Dot — broken out by persona, not the marketing-page minute.
Solo desktop user: expect a short install from the GitHub beta plus the Mistral 7B model download before first use — budget the download time as the main variable, then you are offline-capable. Teams: not applicable, Dot has no shared workspace to stand up.
Switching to or from Dot
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From ChatGPT file uploads: save the files you would have attached, load them into Dot's document mode instead, and keep sensitive work on the machine.
- →From NotebookLM: move your source PDFs and sheets into a local Dot session and accept the loss of shared notebooks and web-grounded answers.
- →From a cloud PDF-chat tool: download your documents, uninstall the cloud dependency, and run the same questions through Dot offline.
- ↗To NotebookLM: upload the same sources to a shared notebook when you need collaboration and web-grounded answers more than local-only processing.
- ↗To ChatGPT file uploads: move your documents to a cloud account when zero-install convenience and current web information matter more than data sovereignty.
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Dot”, and we withheld 6: 6 could not be judged, because “Dot” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Dot.
Official links
Tools that pair well with Dot
Common stack mates teams adopt alongside Dot, with the specific reason each pairing earns its keep.
Deepchat
Open-source, local-first desktop AI client that connects to multiple model providers and keeps your data on your machine.
Atomic Chat
Atomic Chat runs 1,000+ local LLMs offline on your own hardware — free, open-source, no account, no rate limits.
Enclave
Enclave runs open-source AI models locally on your iPhone and Mac for private, fully offline AI chats.
Featured Head-to-Head Comparisons
Dot vs Praktika
Praktika and Dot serve fundamentally different needs: pick Praktika if you want to practice speaking a new language with AI tutors and get real-time corrections; pick Dot if you need a private, offline AI to chat with your own documents. They don't compete on the same use case.
Dot vs Surge Ai
Choose Dot if you need a free, private, local AI for chatting with your own documents and you're comfortable installing a desktop app. Choose Surge AI if you're an AI research team or enterprise builder that needs expert human feedback for RLHF, red teaming, or complex benchmarks—like those used by Anthropic for Fable 5. These tools serve fundamentally different purposes.
Alternatives to Dot
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Deepchat
Open-source, local-first desktop AI client that connects to multiple model providers and keeps your data on your machine.
Atomic Chat
Atomic Chat runs 1,000+ local LLMs offline on your own hardware — free, open-source, no account, no rate limits.
Frequently Asked Questions
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