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stuntd

Local proxy that learns your app's typed LLM decisions and answers them with a Laya head. Jev and OpenAI compatible.

Details

External ID
1382518952
Source
GITHUB
Company
—
Product
stuntd
Website domain
github.com
Launched
Sept. 23, 2026
Cohort
—
Upvotes
31
Upvotes percentile
0.7332820906994619
Tags
claude-code, distillation, jev, laya, llm, llm-proxy, local-inference, openai-compatible, self-hosted, system-one, typed-decisions, typesafe
Fetched at
Sept. 27, 2026, 5:02 p.m.
Updated at
Sept. 27, 2026, 5:02 p.m.

Enrichment

Theme
decision model runtimes and tools
Vertical
Horizontal
Function
Model & infra
Audience
Developer
AI stance
AI-native
Project type
Hobby / open-source project
Normalized one-liner
local llm caching proxy for typed decisions
Manually corrected
False

Could you build this?

Partial Building an HTTP reverse proxy compatible with OpenAI's API is simple, but dynamically training or fine-tuning local linear/classification heads to reliably predict typed LLM outputs at low latency is non-trivial.

What it would actually take: The system requires an HTTP proxy (e.g., FastAPI, Go, or Rust) that inspects JSON schemas of structured outputs, coupled with an embedding pipeline and lightweight model head (like an on-device linear probing head or small classifier) that learns from previous prompt-output pairs to short-circuit queries. Engineering requires expertise in fast local inference (ONNX/TensorRT), embedding distillation, and strict caching/uncertainty-threshold estimation.

Competitors

Other products that read as similar to this one — 533 launches clear the similarity bar, closest 8 shown.

Attention rank: #163 of 534 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 328 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.