Nicheloom

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

LUML

an open source (Apache 2.0) MLOps/LLMOps platform

Details

External ID
46871777
Source
HN
Company
—
Product
LUML
Website domain
github.com
Launched
Feb. 3, 2026
Cohort
—
Upvotes
7
Upvotes percentile
0.38207547169811323
Tags
—
Fetched at
Sept. 7, 2026, 9:26 p.m.
Updated at
Sept. 7, 2026, 9:26 p.m.

Description

Hi HN,We built LUML (https://github.com/luml-ai/luml), an open-source (Apache 2.0) MLOps/LLMOps platform that covers experiments, registry, LLM tracing, deployments and so on.It separates the control plane from your data and compute. Artifacts are self-contained. Each model artifact includes all metadata (including the experiment snapshots, dependencies, etc.), and it stays in your storage (S3-compatible or Azure).File transfers go directly between your machine and storage, and execution happens on compute nodes you host and connect to LUML.We’d love you to try the platform and share your feedback!

Enrichment

Theme
database infrastructure and developer tools
Vertical
Horizontal
Function
Data infrastructure
Audience
Developer
AI stance
AI feature
Project type
Commercial product
Normalized one-liner
mlops and llmops platform
Manually corrected
False

Could you build this?

Partial Standard CRUD dashboards for metrics and model registries are vibe-codeable, but robust distributed ML artifact tracing, lineage tracking, and production model serving infrastructure require specialized distributed systems engineering.

What it would actually take: Building an MLOps platform like MLflow or LUML entails a distributed control plane (Go or Python/FastAPI), an object storage layer with strict immutable versioning (S3/MinIO), and a Kubernetes-based execution runner for deployments (KServe or custom Envoy proxies). The difficult components are real-time telemetry ingestion pipelines under heavy load and building self-contained runtime environments with hermetic packaging. It requires senior infrastructure and MLOps platform engineers.

Discussion

2 comments analyzed.

Competitors mentioned: MLFlow

Concerns raised: MLFlow difficult to self-host for larger teams, Unclear how this differs from MLFlow

Competitors

Other products that read as similar to this one — 52 launches clear the similarity bar, closest 8 shown.

Attention rank: #35 of 53 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 95 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a data infrastructure tool for Media & entertainment yet.