A 150M model that extracts verbatim evidence spans for RAG, no LLM call
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HN · launched Jun 10, 2026 · 6 upvotes (top 69%) · 0 views
Niche: semantic search and rag tools · 93 launches, 0 in the last 7 days · Explore this niche →
Category and tags
- Horizontal
- Search & retrieval
- Developer
- AI-native
- Commercial product
Visit website ↗ Source listing ↗
More like this: all 93 launches in semantic search and rag tools →
Could you build this?
No This involves creating and training a custom 150M parameter ModernBERT-based token classification model for span extraction, requiring deep ML research, curated training datasets, and GPU training infrastructure.
What it would actually take: Requires collecting and annotating tens of thousands of RAG question-context pairs with exact token-level evidence spans, designing the token-classification architecture on ModernBERT, setting up distributed PyTorch training routines with evaluation benchmarks, and exporting optimized ONNX/Safetensors runtimes. This requires specialized ML engineering expertise and significant GPU compute.
Discussion
No comments on this launch.
Competitors
Other products that read as similar to this one : 1899 launches clear the similarity bar, closest 8 shown.
Attention rank: #1285 of 1900 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).
Launched 223 days after the earliest competitor.
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