proomt

Search

Search posts, papers, and topics

All posts

Freek Van der Herten6 min readintermediate

★ Detecting spam and auto-replies with Jev and the Laravel AI SDK

Read on freek.dev

Summary

Jev is a "System One" AI model focused on classification, providing calibrated probabilities for predefined answers rather than generating text. This article demonstrates its use with the Laravel AI SDK to replace complex rule-based systems for detecting spam and auto-replies in a helpdesk application.

  • Jev is a classification-only AI, returning probabilities for predefined answers (Boolean, Choice, Score), unlike generative LLMs.
  • Probabilities are calibrated, meaning a 0.9 score indicates a ~90% chance of being correct.
  • Multiple classification questions can be batched into a single request, processed in parallel, and cost the same as one.
  • It was used to replace a complex system of header checks and subject prefix lists for spam and auto-reply detection.

Engineers needing reliable, structured text classification should consider Jev as a focused, cost-effective alternative to general-purpose LLMs, particularly for tasks like content moderation or message routing.

7/10
llmmachine learningapi designphplaravelspam detection

Related reading

  1. TypeSafe AI's Jev now available on AI Gateway

    Vercel AI Gateway now offers Jev, a probabilistic decision model that returns typed choices, scores, and booleans instead of raw text. TypeSafe AI reports it runs up to 193× faster and 445× cheaper than standard LLMs, exposed via the experimental evaluate API in AI SDK 7.

    Vercelvercel.com2 minrelease

  3. Introducing System One Models and Jev

    TypeSafe AI announced its first “System One” model, Jev, a non‑text‑generating LLM that outputs type‑safe structured decisions with calibrated probabilities. It claims 40‑200× lower latency (70‑500 ms) and 100‑500× lower cost versus frontier LLMs, no hallucinations, and parallel sampling. The post includes a side‑by‑side demo, a custom “workflow” benchmark comparing Jev to GPT‑5.6/6 and other mod…

    Hacker News front pagetypesafe.ai9 minHN1824480lobste.rs26

  4. Reverse-engineered Jev-like model

    Jevlike is an open‑source starter model that scores a list of text options in a single forward pass. It provides a minimal architecture (option queries, shared dot‑product scorer), synthetic data generation, training/evaluation CLI, and examples on Doom and chess. The repo supports a byte‑level encoder or a frozen Hugging‑Face encoder (e.g., Qwen2.5‑0.5B), runs on CPU/MPS/CUDA, and reports benchm…

    Hacker News front pagegithub.com4 minreleaseHN16224

  5. I turned Jev into a (lousy) chatbot

    jevchat is a Python CLI that turns the Typesafe Jev API into a symbol‑level chatbot by repeatedly asking Jev which next character to emit. It offers interchangeable sampling strategies and alphabets, live generation stats, and a benchmark mode that quantifies performance trade‑offs.

    Hacker News front pagegithub.com5 minHN17048

  6. Jev is the fastest-adopted model in AI Gateway history

    Vercel reports that the Jev decision model was adopted by 13% of paid teams within its first day, outpacing prior model launches. Jev claims to be up to 194× faster and 445× cheaper than general‑purpose LLMs while returning structured, probabilistic decisions.

    Vercelvercel.com1 minHN21