What is Simple Jev?
Simple Jev converts contextual inputs into structured, machine-readable decisions using open language models. It accepts single messages, chat histories, and images as context and returns choices, confidence scores, probabilities, and answers in JSON.
Scores are derived from model token probabilities to rank allowed labels and compute confidences without a separate classifier head. The API and interactive playground let you send scenarios, pose multiple questions per request, and retrieve structured responses for downstream code.
RFDT (Really Fancy Decision Training) fine-tunes decision outputs by supplying labeled examples or using a larger teacher model to generate labels. An open-source implementation and documentation, plus demos and sample code, enable integration and experimentation.
Simple Jev pricing
FreeVerify on the official pricing page.
Get started freeSimple Jev's key features
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Accepts single messages, chat histories, and images as context
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Returns choices, confidence scores, probabilities, and answers in JSON
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Derives label rankings and confidences from model token probabilities without a separate classifier head
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Provides an API and interactive playground supporting multiple questions per request and retrieval of structured responses
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RFDT fine-tuning using labeled examples or a larger teacher model to refine decision outputs
Simple Jev use cases
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Convert customer support messages, chat histories and screenshots into structured JSON decisions with Simple Jev, producing ranked resolution choices, token-based probabilities and confidence scores for automated triage, SLA routing and analytics without manual labeling
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Create an explainable compliance and audit trail by extracting contextual decisions from legal, clinical or financial conversations and images using Simple Jev’s LLM decision API and interactive playground, storing token-probability-ranked labels, human-readable answers and provenance for review
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Fine-tune decision outputs for product recommendations or incident prioritization with Simple Jev’s RFDT support and multimodal inputs, then deploy via API to deliver calibrated, ranked recommendations and run A/B testing and continuous improvement
Simple Jev user reviews
Based on 1 review, 100% of users recommend Simple Jev, rated highly for quality results.
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Who is Simple Jev for?
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Machine learning engineers
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Data scientists
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Nlp researchers
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Software developers building ai-driven products
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Mlops engineers
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Product managers for ai products
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Ai/ml startup founders
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Research scientists in ai
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Ai consultants and solution architects
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Educators and students in ai