Nicheloom

Market intelligence for builders — see what's gaining traction before it's crowded.

jevcal

Stop guessing confidence thresholds: calibrate, threshold, and drift-check typed decision models (TypeSafe Jev) against an LLM teacher.

Details

External ID
1375491494
Source
GITHUB
Company
—
Product
jevals
Website domain
github.com
Launched
Sept. 18, 2026
Cohort
—
Upvotes
10
Upvotes percentile
0.28183448629259544
Tags
calibration, confidence-thresholds, jev, llm-evals, system-one, typesafe
Fetched at
Sept. 22, 2026, 1:02 a.m.
Updated at
Sept. 22, 2026, 1:02 a.m.

Enrichment

Theme
decision model runtimes and tools
Vertical
Horizontal
Function
Observability & eval
Audience
Developer
AI stance
AI-native
Project type
Commercial product
Normalized one-liner
model calibration and drift checking tool for typed decision models
Manually corrected
False

Could you build this?

Partial The CLI wrapper, prompt pipeline, and statistical reporting can be vibe-coded, but implementing statistically sound calibration algorithms (e.g., Platt scaling, isotonic regression, ECE calculations) and dataset drift detection for structured LLM decision models requires machine learning domain knowledge.

What it would actually take: The tool requires a Python or TypeScript library implementing probability calibration methods (Platt scaling, temperature scaling, binning algorithms like Expected Calibration Error) comparing smaller typed models to an LLM evaluator. The hard part is mathematically robust confidence calibration, confidence interval estimation under distribution shift, and handling multi-class/structured schema outputs. It requires an applied machine learning practitioner with knowledge of uncertainty quantification.

Competitors

Other products that read as similar to this one — 816 launches clear the similarity bar, closest 8 shown.

Attention rank: #571 of 817 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 322 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a observability & eval tool for Media & entertainment yet.