N71

N71 creates a shared knowledge graph for knowledge workers using multiple AI agents. It connects tools like Notion and email so agents read the same context over MCP. This prevents users from re-explaining projects in every new chat.

N71

About N71

N71 is an AI infrastructure tool that creates a shared context for multiple AI agents. It builds a living knowledge graph from various workplace tools. Agents read from this graph via the Model Context Protocol to maintain continuous context across different chats.

Review

Knowledge workers often switch between different AI agents and lose their project context in every new chat. N71 addresses this by mapping people, projects, and decisions into a single graph. This graph updates automatically as connected tools change.

Key Features

  • Connects tools like Notion, email, calendar, and code repositories to build a living knowledge graph without moving the underlying data.
  • Routes agent interactions through the Model Context Protocol so applications like Claude, Cursor, and ChatGPT read from the same context.
  • Resolves entity identities using behavioral history instead of simple string matching to handle renames and duplicates.
  • Tracks fact evolution over time and flags contradictions when two sources present conflicting information.
  • Assigns confidence scores and source pointers to agent writes, preventing a single bad extraction from poisoning the graph.

Pricing and Value

N71 includes free options and a Pro membership tier. Exact monthly costs are not yet defined. New users can apply a launch code to receive two months off the Pro plan.

Pros

  • Maintains data locality through direct reads from connected tools without extracting raw data.
  • Historical context stays intact.
  • Includes source citations and confidence scores in its responses so users can verify the origin of generated answers.

Cons

  • The tool is not well suited for users who need strict, row-level permission enforcement across different user roles within a single graph.
  • Deletion propagation remains an unsolved problem.
  • Reading agents must actively process confidence scores to discount shaky facts, as the system hands back the score rather than filtering it server-side.

N71 fits teams that orchestrate multiple AI agents and need to eliminate repetitive context briefing. It works best for organizations with interconnected project data.



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