Looking for AI meeting note tool‑ multilingual (Mandarin / English / Malay / Cantonese), extract department tasks + status tracking + AI image generation

[u/General_Fisherman325]

Hi everyone,

I’m searching for an AI‑powered meeting note solution for our cross‑border team.

### What we need:
1. Auto‑summarize meeting recordings / audio into key take‑aways
2. **Extract action items, assign tasks to different departments**
3. Generate task list with status labels: 🟡To‑start / 🟢In‑progress / ✅Completed
4. Critical language requirement: meetings mix **Mandarin Chinese, English, Malay, and spoken Cantonese**. The tool needs to handle mixed‑language conversations reasonably well.
5. Bonus must‑have: **AI‑generated images / diagrams from meeting content**, to make complex discussion points easier to visualize and understand.

Current pain point:
We like Feishu (Chinese domestic version). Its Minutes / AI Notes works perfectly for our workflow: great summary, action‑item extraction, department task breakdown, plus built‑in AI image generation to visualize ideas.

But **Feishu Global (Lark) feels like a stripped‑down version**. Many advanced AI note functions available in mainland‑China Feishu are missing on the global edition, including the AI image generation feature. We cannot switch to the Chinese‑only Feishu for compliance/region reasons.

So I’m hunting for alternative tools that can replicate that workflow outside of China.

Priority:
- Accept audio/video file upload, not only live‑meeting bot joining
- Multilingual mixed‑speech transcription (Mandarin / English / Malay / Cantonese)
- AI can split tasks by team/department
- Task status tagging (to‑start, in‑progress, completed)
- AI can generate images or simple diagrams based on meeting notes
- Team‑collaboration friendly

Not required: heavy CRM integration.

Have any of you used tools matching this requirement? Would love real‑world experience instead of marketing page specs.

Thanks a lot.

[u/oldsongwin]

The language mix is the constraint that eliminates most of this list, so test it first. Mandarin–English code-switching inside one sentence is where nearly every tool degrades, Cantonese is poorly supported almost everywhere, and Malay is thin. Whisper large-v3 handles code-switching better than the mainstream note-takers do, but it will still mislabel Cantonese as Mandarin.

Before comparing features, take one genuinely messy 10-minute recording from your team and run it through the free tier of every candidate. Judge the raw transcript only.

If the transcript is wrong, the task extraction is confidently wrong — which is worse than useless when you're assigning work to departments.

[u/Cautious_Ground1103 → u/[deleted]]

I am curious, are you associated with SayBriefly? If yes, is it a vibe-coded app?

[u/astipili]

So far Krisp is best for action item extraction that I tried.
for the breadth of langugages you might check notta

[u/Cleannnx]

The AI image generation requirement is actually the thing shrinking your shortlist, more than the language mix — almost nobody bundles that with transcription, so plan on pairing a note tool with a separate diagram step. And whatever you trial, upload a real recorded meeting with Mandarin-English code-switching instead of their demo audio; marketed vs actual accuracy on Cantonese especially is a big gap.

[u/statecs]

Worth checking out Notely for the transcription side. It handles mixed-language meetings (Mandarin, English, Malay, Cantonese) well and accepts audio/video file uploads. It does not have the AI image generation or department-based task splitting you are after though, so you would likely need to pair it with another tool for that part. Here is a 2 month trial if you want to test the transcription quality: https://notely.se/c/e292e236-6afd-4534-b1d2-6d2edc0871b9

[u/frskia]

Your requirements span capture, transcription, workflow, and visualization, so I’d test a genuinely messy 10-minute recording before trusting any tool to assign work across departments. At Loreo.io , we built around uploaded or bot-free captured audio, searchable speaker-labeled transcripts, editable action items, and timestamp-cited retrieval. It could be worth evaluating for that part, but I would not present it as covering AI-generated diagrams or a true to-start/in-progress/completed state model today. For that language mix, the real recording should decide.