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Kairo

Fail-closed LLM inference routing from RTX 5090 measurements

Details

External ID
49691112
Source
HN
Company
—
Product
Kairo
Website domain
github.com
Launched
Sept. 14, 2026
Cohort
—
Upvotes
5
Upvotes percentile
0.12998405103668262
Tags
—
Fetched at
Sept. 18, 2026, 5:02 p.m.
Updated at
Sept. 18, 2026, 5:02 p.m.

Enrichment

Theme
ML inference and model optimization
Vertical
Horizontal
Function
Model & infra
Audience
Developer
AI stance
AI-native
Project type
Commercial product
Normalized one-liner
fail-closed inference router for llms
Manually corrected
False

Could you build this?

Partial The routing logic and web service are manageable, but gathering empirical latency/throughput profiles on specific hardware (RTX 5090) and designing fail-closed routing policies requires systems benchmarking expertise.

What it would actually take: Requires an LLM proxy gateway (written in Go or Rust) that ingests real-time hardware telemetry and latency profiles from dedicated GPU testbeds running inference engines (e.g., vLLM or TensorRT-LLM). The hard part is implementing sub-millisecond fail-closed routing algorithms and continuous active probing under dynamic GPU load conditions.

Discussion

No comments on this launch.

Competitors

Other products that read as similar to this one — 1176 launches clear the similarity bar, closest 8 shown.

Attention rank: #953 of 1177 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 318 days after the earliest competitor.

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