devwithjev
— reading now— views
Submit a build

Arabic-English Market News Classifier

The author built a test to classify market news as important, uncertain, or noise, then identify its direction and event type. The test covered 30 industry cases in Arabic and English from the Saudi and U.S. markets.

سامي المحيميد | مستشار تطوير أعمال@SamiBizConsult𝕏
180 طلب كشفت لي أن سؤال: «أي نموذج أفضل؟» كان السؤال الخطأ. بنيت اختبار لفرز أخبار السوق إلى: مهم، غير مؤكد، أو ضوضاء. ثم تحديد اتجاه الخبر ونوع الحدث. الاختبار شمل 30 حالة صناعية بالعربية والإنجليزية، من السوقين السعودي والأمريكي، وشغّلت كل حالة 3 مرات على كل نظام. النتيجة: ـ TypeSafe حقق 100% في تصنيف الإشارة، و100% في الثبات، بمتوسط 0.384 ثانية. ـDeepSeek Flash كان أدق في التفاصيل: 85.6% للنتيج
Sep 22, 2026X postsView on X
The source reports results for TypeSafe and DeepSeek Flash but does not identify Jev as a system used in the test.

Also filed under Triage & routing

  • Jev-Powered Self-Healing for Pistachio

    Pistachio uses Jev to triage logged errors and categorize them as GitHub issues as part of its self-healing error and bug-handling workflow.

  • Identifies Canadian Federal Tax Documents

    Emile Riberdy built a demo using Jev in Avalanche to identify Canadian federal tax documents. It takes ~1 second and costs less than 1 cent per document.

  • How to Build Things with Jev & OpenJevs

    How to Build Things with Jev & OpenJevs In this video, we build a model router using both the API-based original Jev and also using Semif. ‍ Github: code will be up in ...

  • Jev is HERE. How to use it

    Jev is HERE. How to use it In this episode, I talk with Ryan Vogel about Jev, a new type of AI built for classification. Ryan shows how Jev takes an input plus ...