Layer AI
Metadata store for production ML
Layer AI launched on May 7, 2022 with 124 votes, #221 of 2,942 launches that month and more than 90% of that year's launches. The site was still online in September 2026, 4 years on.
What it does
Build, train and track all of your machine learning project metadata including ML models and datasets with semantic versioning, extensive artifact logging and dynamic reporting with local↔cloud training.
The creative harness for brand-differentiated content. Generate images, video, 3D and audio with 300+ models, train Layer on your style, automate production.
Layer learns your brand, your style, and the work you have already shipped, so your creative passes review the first time. Attachments, projects, reference sets and voice are part of your workspace. Generate, edit, train and automate across image, video, 3D and audio, with 300+ models behind it and the applied knowledge of which one to reach for. New models arrive integrated, so the foundation stays current without your team doing anything. Give the Creative Agent a brief and it researches, picks the model, generates and refines — with you in the loop at every step. Train Layer on your own artwork with custom LoRAs and reference sets, then edit precisely — mask, inpaint, relight, remesh,…from layer.ai
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Metabase Data StudioMar 2026 · metabase.com · ▲153Build the semantic layer that makes AI analytics trustworthy
Cortex – machine learning infrastructure for developers2019 · github.com · ▲86Production infrastructure for machine learning at scale - cortexlabs/cortex


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