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What is Jev?
Jev is a low-latency System One Model from TypeSafe AI built for structured decision-making rather than open-ended text generation. TypeSafe describes System One Models as a new class of frontier models intended to make fast decisions that can be consumed directly by application code. Jev takes unstructured information as input and returns predefined typed outputs with probabilities and confidence scores instead of generating unrestricted natural-language strings. Its parallel sampling architecture produces outputs in a single query rather than sequentially generating one token at a time, which is designed to reduce latency and inference cost. The model is trained with Reinforcement Learning for Calibrated Decisions, which focuses on producing well-calibrated probabilities for structured System One tasks. TypeSafe positions Jev as a software-native intelligence layer for tasks including classification, routing, scoring, extraction, decision branching, and other workflows that benefit from probabilistic logic. It can also be applied to model evaluation and safety workflows by scoring, judging, verifying, guardrailing, or detecting jailbreaks in prompts, reasoning traces, and generated outputs. The company reports service response times of roughly 70 to 500 milliseconds and says this can make Jev suitable for interactive and real-time applications where traditional frontier models may introduce too much latency. Jev is designed to return consistent schemas without type errors, allowing its results to be incorporated into code without the same parsing and validation steps commonly required for free-form LLM responses. TypeSafe also highlights map-reduce style processing over large datasets as a potential use case, where the model can turn large amounts of unstructured information into structured features and insights.
What is Hume Audio Decisions API?
The Hume Audio Decisions API is a cloud-based tool designed specifically for developers who are working on voice applications and for teams that are involved in sound and speech analysis. This API is capable of processing audio recordings, along with optional contextual details and user questions, to provide structured probabilities regarding possible answers. Users can inquire about various aspects of audio, including the number of speakers and background noise, as well as subjective evaluations of tone, empathy, clarity, naturalness, and frustration levels. By harnessing these insights, teams are empowered to review support calls, evaluate the performance of voice agents and text-to-speech systems, label speech datasets, compare different recordings, and identify cases needing escalation or further model refinement. Furthermore, the API functions as a decision-making layer that can be easily integrated with existing speech recognition and voice synthesis systems, allowing developers to embed its analytical scores and probabilities into their specific workflows. Access to this API is managed by Hume, with pricing based on the volume of audio clips, inquiries, and contextual tokens submitted. Its adaptability across various fields highlights its potential to improve user experiences and enhance operational productivity, making it a valuable asset for organizations aiming to leverage audio data effectively. Ultimately, the Hume Audio Decisions API stands out as a versatile solution that not only aids developers but also contributes to advancing the overall quality of voice interactions.
Integrations Supported
API Availability
API Availability
Has API
Pricing Information
Input: $0.042 / 1M tokens
Input tokens: $0.042 / 1 million tokens ($42 per billion tokens).
Output tokens: FREE (too cheap to meter).
Output tokens: FREE (too cheap to meter).
Pricing Information
$0.47/1M tokens
Usage costs $0.47 per 1 million input tokens, with no commitment. An organization receives a 1-million-input-token trial credit after access is granted. Enterprise plans offer volume pricing and deployment in a VPC, on premises, or in country.
Supported Platforms
SaaS
Supported Platforms
SaaS
On-Prem
Customer Service / Support
Web-Based Support
Customer Service / Support
Web-Based Support
Training Options
Documentation Hub
Training Options
Documentation Hub
Company Facts
Organization Name
TypeSafe AI
Date Founded
2024
Company Location
United States
Company Website
typesafe.ai/
Company Facts
Organization Name
Hume AI
Date Founded
2021
Company Location
United States
Company Website
www.hume.ai/products/decision-model-api
Categories and Features
AI Decision Models
Not specified
AI Models
Not specified
Categories and Features
AI Decision Models
Not specified