Papr is a predictive memory platform for AI that combines vector embeddings and knowledge graphs in a simple API. It enables AI assistants to remember context across sessions, improving accuracy and enabling complex workflows like multi-hop retrieval and intelligent support.
Freemium
$20/mo
How to use Papr?
Integrate Papr via its Python or TypeScript SDKs or MCP to add memory to your AI applications. Ingest data from sources like chats, PDFs, or tools, then use its retrieval and reranking features to build assistants that maintain context, support agents that remember past issues, or research tools that connect concepts across documents.
Papr 's Core Features
Ingest data from any source including chat conversations, PDFs, videos, documents, and tools like Slack, GitHub, and Jira with real-time synchronization.
Extract smart chunks, entities, embeddings, and create knowledge graphs to structure and understand complex information relationships.
Store permission-aware vector embeddings and knowledge graphs with dynamic indexing for secure and efficient data management.
Retrieve information using advanced techniques like query expansion, hybrid search, and efficient multi-hop retrieval for accurate context fetching.
Rerank search results intelligently using relationship and semantic matching, relevance scoring, and contextual filters to prioritize the most relevant data.
Cite sources with tracking for easy verification, fact-checking, and audit trails to ensure transparency and reliability in generated content.
Power any LLM, agent, or tool with flexible APIs, MCP, or UI components, enabling seamless integration into various AI workflows.
Papr 's Use Cases
Travel assistants that remember user preferences like aisle seats for family bookings, enabling personalized and consistent service across sessions.
Customer support agents that recall past issues, such as a known camera bug, to provide quick and accurate solutions without repeating troubleshooting steps.
Financial analysts querying documents to connect concepts like APAC CapEx trends after a CEO pivot, saving hours of manual research.
Healthcare professionals using patient history and treatment patterns to check drug interactions, improving safety and decision-making in patient care.
Legal researchers applying precedent and context from cases like Smith v. Jones to determine relevance, streamlining case preparation and analysis.
Authors maintaining narrative consistency in stories by tracking character skills, such as ensuring a lockpicking scene aligns with earlier plot points.
Developers building AI chat apps like Pen that remember conversations, allowing users to resume discussions seamlessly without losing context.
Papr 's Pricing
Free
$0
Basic AI chat functionality with 50 interactions, 100 memories storage, and 20 searches per month.
Starter
$20/mo
Enhanced AI capabilities with 1,000 basic interactions, 200 premium interactions, 5,000 memories storage, and 1,000 searches per month.
Pro
$200/mo
High-volume access with unlimited basic interactions, 3,000 premium interactions, 100,000 memories storage, and 50,000 searches per month.
Enterprise
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Unlimited memories with enterprise-grade features including on-premises deployment, SSO, audit logs, and custom integrations.
