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maria takova
Backend, Data & AI Engineer building production-ready APIs
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maria is ready for their next project!
Hello Ai entusiast. Jev is here 🙌 It isn’t just another classifier—it’s a paradigm shift in how AI makes decisions. While BERT and XGBoost excel at structured tasks, they demand labeled data, training cycles, and ongoing maintenance. Jev, by contrast, delivers calibrated,...
medium.com
Jev in AI: The Paradigm Shift in Structured Decision-Making — Beyond BERT, Beyond XGBoost
In the rapidly evolving landscape of artificial intelligence, one name has sparked both excitement and controversy: Jev, TypeSafe AI’s…
AI-powered FAQ retrieval system for live customer support using hybrid search (BM25 + dense retrieval), reranking, grounding checks, and validation loops to deliver accurate, reliable answer suggestions in real time.Implemented multi-turn query handling, confidence-based...
Hello Contra people.
I am reaching for advice. We want to keep this paper design but make it not looking so plain. Any ideas how to improve it? The full site can be reached at codea.bg
Hi Contra people,
In Codea we work on STR automation and we are looking for few people to test it for free aand give us a feedback. Everyone who managing short term rental is welcome.
Hi Contra people,
As you know RAG/LLM systems look easy in demo mode. The real learning starts when they hit production. 😅
I recently wrote a Medium article sharing some of my lessons learned while building and deploying RAG/LLM systems — the unexpected challenges, trade-offs,...
medium.com
Building an Intelligent FAQ Assistant: The Complete Production RAG Pipeline
Moving an enterprise Retrieval-Augmented Generation (RAG) system from a functional codebase to a resilient production service is…