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Hindsight Models and Inference API

Small, fast models for reranking, embeddings and decisions

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Hosted models for the steps around your LLM: reranking, embeddings and typed decisions. Point your Cohere or OpenAI client at inference.hindsight.vectorize.io and keep your code. hs-rerank-1 and hs-embed-1 are the most accurate small open models on our benchmarks and run fast on a CPU; hs-decide-1-flash answers yes/no, pick-one and how-likely questions in 167 ms, instead of an LLM call. From $0.005 per 1M tokens, $5 free credit, open weights on Hugging Face.

PH · launched Nov 4, 2026 · 73 upvotes (top 2%) · 0 views

Niche: machine learning inference engines · 108 launches, 8 in the last 7 days ▼ -27% · Explore this niche →

Category and tags

  • Horizontal
  • Model & infra
  • Developer
  • AI-native
  • Commercial product
  • API
  • Developer Tools
  • Artificial Intelligence

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Could you build this?

No The product is hosted reranking, embedding, and decision models whose claimed accuracy comes from the vendor's own trained models. Matching that requires ML research, training data, and GPU compute, beyond what vibe coding provides.

What it would actually take: A serving API compatible with Cohere and OpenAI clients is straightforward, but the differentiator is the models themselves. Building competitive small rerankers and embedders means curating large training datasets, running distillation or contrastive training, and benchmarking, which requires ML research engineers and meaningful GPU budget.

Competitors

Other products that read as similar to this one : 466 launches clear the similarity bar, closest 8 shown.

Attention rank: #24 of 467 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 366 days after the earliest competitor.

The niche, labels, vibe code rating and competitor comparison on this page are analysis by Nicheloom. If you use them, please credit nicheloom.com. How you may use our data.