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agent-jev

AgentJev-0.6B - a fast 'System One' decision model for AI Agents: feed it any unstructured state (diffs, traces, logs) and structured questions, get calibrated probability distributions back in one ~50ms forward pass. Zero output-token decoding.

Details

External ID
1380116460
Source
GITHUB
Company
—
Product
agent-jev
Website domain
github.com
Launched
Sept. 21, 2026
Cohort
—
Upvotes
303
Upvotes percentile
0.9772610812195747
Tags
—
Fetched at
Sept. 25, 2026, 5:02 p.m.
Updated at
Sept. 25, 2026, 5:02 p.m.

Enrichment

Theme
local AI inference and runtimes
Vertical
Horizontal
Function
Model & infra
Audience
Developer
AI stance
AI-native
Project type
Hobby / open-source project
Normalized one-liner
fast decision model for ai agents
Manually corrected
False

Could you build this?

No Training a custom 600M-parameter non-autoregressive language/decision model with 50ms forward pass inference requires foundational ML research, curated pretraining/finetuning datasets, and compute infrastructure.

What it would actually take: A builder would need to architect a specialized transformer encoder or non-autoregressive decoder that maps unstructured text directly to softmax classification heads without token-by-token generation. The stack involves distributed PyTorch/vLLM training on hundreds of thousands of agent execution traces, followed by quantization and custom kernel optimization (e.g., TensorRT-LLM) for ultra-low latency execution. This demands core ML engineering and access to GPU training clusters.

Competitors

Other products that read as similar to this one — 498 launches clear the similarity bar, closest 8 shown.

Attention rank: #31 of 499 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 321 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a model & infra tool for Fintech yet.