Papr Graph
API that upgrades the vector embeddings a team already has into graph-aware embeddings: one call at index time attaches 14 relational dimensions (entities, relations, time, ownership) to each vector and one call at query time reranks the top results, keeping the user's embedding model and vector database; processed in memory and not stored, with VPC deployment and audit logs for enterprise teams.
Find alternatives to Papr Graph
What it does
- Vector search
- Knowledge retrieval
Features 4
- Graph-aware embeddingsAttaches relational signals to every vector, such as entities, relations, time and ownership.
- Reranking at query timeReranks top cosine results by scoring candidates' signals against the query's intent.
- Keep your stackWorks with any embedding model and the user's existing vector database.
- Enterprise deploymentVPC deployment, audit logs and custom data processing agreements for enterprise teams.
Sources
- Pricing
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The page offers a free API key and publishes no plan or price.
- Description
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Official documentation · 19 Oct 2026
Papr Graph page: "Papr upgrades the vector embeddings you already have into graph-native embeddings."
- What it does
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Official documentation · 19 Oct 2026
Papr Graph page: "Papr upgrades the vector embeddings you already have into graph-native embeddings."
- Sold within
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The page offers a free API key; no plans or prices are published.
- Name
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Official documentation · 19 Oct 2026
Name as published on the product page.
- URL
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Official documentation · 19 Oct 2026
Product page, read 2026-10-19.
- Deployment
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Official documentation · 19 Oct 2026
The pages read state no deployment model beyond the vendor-run service; saas is recorded as the vendor-operated reading.
- Interfaces
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Official documentation · 19 Oct 2026
Papr Graph page: integration is an API key plus papr.transform and papr.rerank calls; the home page links Python and TypeScript SDKs.
Also from Papr
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Papr Work Application
Local desktop application where users describe a sales, marketing or customer workflow in chat and AI agents build it as an app that keeps running, connected to calendar, email and CRM tools and to the user's choice of model (ChatGPT, Claude, Gemini, Grok or a local Ollama model); offered through a waitlist and no price is published.
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