AI assistants and search decision
Deeptrue
A competent developer can build a useful real-time meeting translation copilot in about a week using existing speech/translation APIs and the cited open-source projects as references, so building is realistic unless you need the vendor's undisclosed integrations or enterprise SLAs.
Visit website↗Not priced
No pricing page we fetched carried a figure, so there is nothing to compare against. The build side is still real.
$100one-off32 h to build
$50/mo3 h/mo upkeep
No published price to break even against.
Open-source builds that already do this
Every project below is open source and already does this job today. Fork one, self-host it, or take the parts you need - the build prompt further down assumes an empty file, and this is the shortcut past that. Licences differ; check the one on each card before you ship. All Deeptrue alternatives, with the arithmetic →
What a replacement has to do
- Capture meeting audio → transcribe streaming speech → translate transcript in real time → synthesize or display translated captions to meeting participants
What it still won’t have
- Polish and UX refinements of a commercial product
- Prebuilt integrations for many meeting platforms (e.g., Zoom marketplace app)
- Any proprietary models, optimizations, or latency tuning the vendor may have
- Brand trust, support SLAs, and managed deployment
What remains hard
- Product polish and ongoing maintenance
First-year cost
No published price
Deeptrue does not publish a price we could read, so there is nothing to compare against. What building costs is below.
Money you would actually spend
Time you would spend
—
What you would spend
What we assumed
The verdict above measures whether you could build it. This one is only about money.
Runnable build prompt
Build a minimal real-time meeting translation copilot using Node.js (Express) + WebRTC for audio capture/relay, a Python FastAPI service for transcription/translation orchestration, and PostgreSQL for lightweight settings. Core features: 1) join a browser meeting page and capture mic + system audio via WebRTC; 2) stream audio to a transcription service (configurable: commercial API or local model); 3) stream translated captions back to the client with language selection and basic latency monitoring; 4) optional TTS of translated output; 5) user settings and logs in Postgres; 6) authentication via OAuth2. Out of scope: marketplace app packaging for Zoom/Teams, advanced latency optimization, proprietary model training. Provide error handling for network/stream failures, end-to-end tests for stream flows, and deployment scripts (Docker + Kubernetes manifest or single-node Docker Compose).
How we checked
How the score was reached
- Build verdict base78
- An open-source build was found+5
- 3 cited sources+3
- Evidence score86
The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time - so the same evidence always produces the same number.
How scoring works →Cited sources · 3
Every page the run actually retrieved.
- official productDeeptrue homepage
- open sourceniedev/RTranslator
- open sourceSakiRinn/LiveCaptions-Translator
Integrity checks
What held up, and what did not.
