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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Jev is TypeSafe AI’s first public System One Model, a class of AI designed to make fast, structured decisions that software can consume directly. Instead of generating arbitrary strings like a traditional large language model, Jev produces predefined type-safe values accompanied by calibrated probabilities and confidence estimates. Its architecture generates outputs in parallel rather than autoregressively producing one token at a time, allowing the model to prioritize speed and computational efficiency. TypeSafe trains Jev using Reinforcement Learning for Calibrated Decisions, an approach intended to optimize for accurate uncertainty estimates and consistent structured outputs. The model can be embedded into conventional software as an intelligent decision layer for classification, scoring, routing, extraction, branching, and other tasks where hand-written rules would be too rigid. Jev can also be used to judge, verify, guardrail, or detect problematic behavior in outputs from other AI systems. TypeSafe reports typical end-to-end response times between 70 and 500 milliseconds and positions the model for applications where low latency is important. The company also emphasizes schema guarantees, meaning Jev’s outputs are constrained to the structures defined by the application rather than requiring developers to parse and validate unrestricted generated text. Jev is aimed at developers and organizations building automation, real-time software, large-scale data workflows, and production systems that require dependable structured AI decisions.

Description

Span-01 is an advanced hyper-parallel reasoning classifier that identifies intricate patterns within extensive production traces in a single forward pass. Instead of producing tokens one after the other, it analyzes natural-language behavior definitions and provides direct probabilities indicating whether a behavior is present, absent, or not observable. The model undergoes initial training for general classification reasoning using Reinforcement Learning with Human Feedback (RLAIF) before it is fine-tuned specifically for behavior detection. This allows Span-01 to utilize previously unseen definitions for new behaviors and various domains, avoiding limitations imposed by a rigid taxonomy. During the inference phase, its hyper-parallel definition branches assess multiple behaviors simultaneously against the same trace context, and the incorporation of hybrid attention facilitates effective reasoning over lengthy and intricate inputs. Span-01 is meticulously crafted for monitoring production environments with a focus on safety, reliability, grounding, agent behavior, and response quality, addressing challenges such as jailbreak and prompt injection detection, as well as privacy and confidentiality concerns. Its innovative approach positions Span-01 as a significant advancement in the field, enabling more efficient and comprehensive analysis of complex behaviors.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

AssemblyAI No 
Cognee No 
Google GenAI SDK No 
JavaScript No 
LangChain No 
LinkUp No 
LlamaIndex No 
Mastra AI No 
Mem0 No 
OpenAI No 
OpenAI Agents API No 
PostHog No 
Python No 
TypeScript No 
Vercel No 

Integrations

AssemblyAI Yes 
Cognee Yes 
Google GenAI SDK Yes 
JavaScript Yes 
LangChain Yes 
LinkUp Yes 
LlamaIndex Yes 
Mastra AI Yes 
Mem0 Yes 
OpenAI Yes 
OpenAI Agents API Yes 
PostHog Yes 
Python Yes 
TypeScript Yes 
Vercel Yes 

Pricing Details

Input: $0.042 / 1M tokens
Input tokens: $0.042 / 1 million tokens ($42 per billion tokens).

Output tokens: FREE (too cheap to meter).
Free Trial No 
Free Version No 

Pricing Details

$199 per month
Free Trial Yes 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Vendor Details

Company Name

TypeSafe AI

Founded

2024

Country

United States

Website

typesafe.ai/

Vendor Details

Company Name

Respan

Founded

2023

Country

United States

Website

www.respan.ai/blog/introducing-span-1

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