Arguium Reviews and Details

Questions & Answers

1. What makes Arguium unique?

   Arguium helps during the conversation rather than after it, and it never joins the call to do so.

   Most meeting AI tools connect to the meeting as a bot participant: they appear in the participant list, need admitting, and often trigger a recording notice. Arguium runs locally as an always-on-top overlay and captures system audio at the operating-system level, so nothing appears in the participant list and stealth mode keeps it out of your own screen shares. Because it captures below the platform, Zoom, Microsoft Teams, Google Meet, Slack huddles, Webex and in-person conversations all behave identically, with no per-platform integration.

   It also reads the screen, not just audio. You can capture a region or the whole screen, queue several captures, and ask a single question spanning all of them.

   Finally, the privacy model is configurable rather than promised: use the hosted models, supply your own Gemini or OpenAI API key so requests go straight to your provider account, or point it at a local Ollama model so no prompt, screenshot or transcript leaves your machine.

2. Why should a person choose Arguium over its competitors?

   It depends on what you actually need, and it is worth being straight about that.

   If you want an archive of team meetings that everyone has agreed to record, a bot-based notetaker like Otter.ai is the better tool: it keeps recording after you close your laptop, it can cover meetings you did not attend, and joining as a participant gives it cleaner per-speaker audio. If you want a genuinely good written record your colleagues can search, that is what Granola is built for.

   Choose Arguium when the value is in the conversation itself. Notes arrive after the decision was made; the thirty seconds where you needed the number, the objection response, or the name you half-remember is where Arguium works. Transcription streams as the sentence is spoken and an answer can begin before the speaker finishes.

   Two other practical differences: being hidden from screen-sharing software is included on every plan here, including the free one, rather than sold as an upgrade; and you can run entirely on your own API key or a local model, so the vendor need not sit in your data path at all.

3. How would you describe the primary audience of Arguium?

   People whose work happens in live conversations, on their own machine rather than through a team workspace.

   In practice that is three groups. Salespeople and account executives, who need a price, an objection response or a competitor comparison while the prospect is still on the call. Anyone in a technical or behavioural interview, where a question needs to be caught accurately and a shared coding screen needs reading under time pressure. And people in everyday client calls, standups and presentations who want a live transcript and answers without a notetaker bot appearing in the participant list.

   It is an individual tool rather than a team platform: sessions are stored encrypted on your own device, pricing is a flat personal rate rather than per seat, and there are no workspace or admin features. Privacy-conscious users are a distinct part of the audience too, since Arguium can run on your own API key or a fully local model.

   Available for macOS and Windows, with the interface and live transcription in English, Spanish, French, German and Portuguese.

4. Which are the primary technologies used for building Arguium?

   The desktop app is Electron with a React 19 and TypeScript renderer, styled with Tailwind and built by Vite. Running as a native desktop process is what makes the always-on-top overlay, global shortcuts, system-audio capture and exclusion from screen sharing possible in the first place; a browser tab could not do any of it.

   Audio goes through an AudioWorklet capture pipeline to a realtime speech-to-text model over a persistent WebSocket, which is why text appears while a sentence is still being spoken rather than after the recording stops. Screenshots are processed locally with Sharp before being sent to a vision model.

   API traffic is proxied through a Cloudflare Worker at the edge, with Durable Objects holding the realtime voice connections, and Firebase handles authentication. Conversation history is stored locally in SQLite, encrypted at rest on the device.

   For the models themselves: Google Gemini and OpenAI are supported out of the box, you can supply your own API key for either, or point the app at a local model served by Ollama for fully offline use.

5. Who are some of the biggest customers of Arguium?

   Honestly: there aren't any, and that is by design rather than a gap we are hoping to fill.

   Arguium is built for one person at a time. There is no workspace, no seat management, no admin console and no shared archive, because the thing it does happens on your machine during your conversation. Sessions are stored encrypted locally rather than in a team account, pricing is a flat personal rate rather than per seat, and you can point it at your own API key or a local model so that nobody, including us, sits in the middle.

   That makes it a poor fit for the sort of company-wide rollout that produces a logo wall. If you need central billing, SSO, org-wide retention policies and a searchable record your colleagues can read, a team-oriented notetaker is the right tool and we would rather say so than pretend otherwise.

   The people using Arguium are individuals: salespeople who need an answer mid-call, candidates in technical interviews, consultants and freelancers on client calls. If that describes you, the free plan is there to try without an account review or a sales conversation.

6. What's the story behind Arguium?

   Arguium started from a narrow observation: almost every AI meeting tool is built around the summary. The value arrives in your inbox once the call is over. That is genuinely useful for records, and useless in the thirty seconds where you needed the number, the objection response, or the name you half-remember.

   So the product was built for the live moment instead, and two decisions followed from that.

   The first was not to be a bot. Joining the call as a participant is the easy way to get audio, but it puts a notetaker in the participant list, needs admitting, and changes the tone of a conversation. Capturing system audio at the operating-system level instead means nothing appears in the meeting, and it works the same on Zoom, Teams, Meet, Slack or across a table, with no integration per platform.

   The second was that a tool which sees your meetings and your screen has to let you decide where that data goes. Hence your own API key, or a local model through Ollama, and session history encrypted on your own machine.

   It is independently built, recently launched, and still early.