TokenPath
token-level citations for LLM output, read from attention
Details
- External ID
- 48997273
- Source
- HN
- Company
- —
- Product
- TokenPath
- Website domain
- tokenpath.ai
- Launched
- July 21, 2026
- Cohort
- —
- Upvotes
- 5
- Upvotes percentile
- 0.1081242532855436
- Tags
- —
- Fetched at
- Sept. 7, 2026, 9:26 p.m.
- Updated at
- Sept. 7, 2026, 9:26 p.m.
Enrichment
- Theme
- ML inference and model optimization
- Vertical
- Horizontal
- Function
- Observability & eval
- Audience
- Developer
- AI stance
- AI feature
- Project type
- Commercial product
- Normalized one-liner
- token-level attribution tool for llm outputs
- Manually corrected
- False
Could you build this?
Partial While standard RAG can be vibe-coded, TokenPath extracts token-level attribution directly from internal transformer attention matrices, which requires hosting open-weight LLMs with custom attention hooks or attribution model pipelines.
What it would actually take: Requires a dedicated GPU inference service (vLLM, HuggingFace TGI, or custom PyTorch) configured to extract cross-attention maps and gradient-based attributions (e.g., Integrated Gradients or Attention Rollout) between source context tokens and output tokens. The hard part is efficiently aggregating dense, high-dimensional attention tensors into coherent span-level attributions at low latency without blowing up GPU memory.
Discussion
No comments on this launch.
Competitors
Other products that read as similar to this one — 484 launches clear the similarity bar, closest 8 shown.
Attention rank: #428 of 485 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).
Launched 265 days after the earliest competitor.
- Tokensift, an open-sourced token-efficiency linter for LLM prompts · hn · 2026-08-29 · 6 upvotes · similarity 0.64
- CTON: JSON-compatible, token-efficient text format for LLM prompts · hn · 2025-11-20 · 13 upvotes · similarity 0.63
- LLM Wiki · hn · 2026-04-06 · 6 upvotes · similarity 0.55
- LLM Attention Visualization · hn · 2026-09-08 · 173 upvotes · similarity 0.55
- Reducing LLM input tokens by 70% · hn · 2026-05-12 · 56 upvotes · similarity 0.54
- A better LLM-wiki with multi-path research [550 stars] · hn · 2026-06-11 · 5 upvotes · similarity 0.53
- A tool to properly observe your LLM's context window · hn · 2025-10-30 · 8 upvotes · similarity 0.52
- BonzAI · hn · 2026-05-22 · 5 upvotes · similarity 0.52
Other launches for this product
- No other launches for this product.
Same idea, different domain
Nobody's really built a observability & eval tool for Media & entertainment yet.