I spent ~10 minutes looking at it. Vibe-coded website. Both bundles contain quantized versions of the CohereLabs/cohere-transcribe-03-2026 model. The model in

I spent ~10 minutes looking at it. Vibe-coded website. Both bundles contain quantized versions of the CohereLabs/cohere-transcribe-03-2026 model. The model in JEXXA.dmg is MLX int8 g64 affine quantized. JEXXA-Small.dmg has the same model but MLX int4 g32 affine quantized. There's also an int8 quantized WeSpeaker ECAPA-TDNN speaker-verification ONNX encoder. No acknowledgments for both models (doesn't the Apache 2.0 license require it? WeSpeaker's cc-by-4.0 license certainly does). Both bundles also contain full-blown Python 3.12.8 runtimes with about a dozen packages installed. Apps are unsandboxed menubar apps and also contain PostHog analytics and Supabase auth. So, I wouldn't run it on any of my machines. A few engineering hygiene issues like a .pytest_cache directory, Python code, .DS_Store files, etc. Given the above, I suspect the "I am training better models." is just marketing speak. nb: The demo link without LinkedIn tracking slop: https://www.linkedin.com/posts/sankyde_jexxa-demo-httpsjexxaorg-ugcPost-7505546140248092672-llql/ https://www.linkedin.com/posts/sankyde_jexxa-demo-httpsjexxa...