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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

ABTestly is a robust A/B testing solution designed for teams that prefer to implement experiments through code rather than a graphical interface. Each variation is crafted using authentic JavaScript and CSS, ensuring that experiments are integrated directly into your code repository and undergo the same rigorous review process as other code modifications. The platform maintains a lightweight runtime of approximately 31 KB when gzipped, and it prevents visitors from experiencing a flash of the control version by holding the page until the variation is fully applied. Instead of relying on a single inferred number, ABTestly meticulously tracks assignment, exposure, and conversion as three distinct events on a precise ledger, enhancing the auditability of results. It provides clear confidence intervals along with the sample size, avoids premature declarations of winning variations, and identifies any sample ratio mismatches, alerting users to potential issues. The platform features three statistical engines: frequentist analysis is available for all plans, while sequential and Bayesian methods are reserved for Pro plans and above. Additionally, it includes a speed guardrail that compares the 75th percentile Largest Contentful Paint (LCP) against the control group, ensuring optimal performance metrics. Transparent pricing is available, with plans starting at $99 per month for up to 50,000 tracked users, $249 for 200,000 users, and $549 for up to 500,000 users, all of which come with a 14-day trial for monthly subscriptions to allow teams to evaluate the service effectively.

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.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

No images available

Screenshots View All

Integrations

No details available.

Integrations

No details available.

Pricing Details

$99/month
Free Trial Yes 
Free Version No 

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 

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) No 
In Person No 

Vendor Details

Company Name

ABTestly

Founded

2025

Website

abtestly.com

Vendor Details

Company Name

TypeSafe AI

Founded

2024

Country

United States

Website

typesafe.ai/

Product Features

AB Testing

Audience Targeting No 
Campaign Segmentation No 
Funnel Analysis No 
Heatmaps No 
Landing Pages / Web Forms No 
Multivariate Testing No 
Split Testing No 
Statistical Relevance Analysis No 
Surveys No 
Test Scheduling No 
Visual Editor No 

Product Features

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No Alternatives

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