N71

Product Introduction

1. Definition: N71 is an enterprise-grade AI orchestration and memory platform. Technically, it is a context management system that builds and maintains a dynamic, shared knowledge graph from connected data sources, accessible to multiple AI agents via the Model Context Protocol (MCP).
2. Core Value Proposition: It exists to solve the pervasive problem of context fragmentation in AI agent workflows. For knowledge workers managing multiple AI agents, N71 provides a single source of truth that updates in real-time, eliminating redundant work and ensuring every agent is operating with the latest context.

Main Features

1. Dynamic Knowledge Graph: N71 automatically constructs a coherent data model from disparate tools. How it works: Users connect sources like CRM, analytics, and internal docs via one-click integrations. The platform ingests this data, identifies entities and relationships, and builds a living knowledge graph. This graph is continuously updated the moment a change occurs in any connected source, ensuring data consistency.
2. MCP-Powered Agent Context: The platform serves its constantly updated knowledge graph to AI agents through the Model Context Protocol (MCP). This means any compatible AI agent (e.g., in a CLI, IDE, or chatbot) can "read" from the shared N71 context, starting any interaction fully informed of prior decisions, changed data, and current priorities without manual briefing.
3. Proactive Thoughts & Workflows: N71 analyzes the knowledge graph to surface automated insights and actions called "Thoughts." These are proactive automations triggered by data patterns. How it works: The system detects scenarios like stale deals, churn risks, or reporting tasks, then generates specific, actionable workflows (e.g., draft re-engagement emails, compile metrics) for human review and one-click execution.

Problems Solved

1. Pain Point: AI agent amnesia and context silos. Each new chat with an AI agent starts from a blank slate, and agents cannot share learnings, leading to repetitive manual context-sharing, inconsistent decisions, and operational lag as priorities change.
2. Target Audience: Technical knowledge workers and operations teams orchestrating multiple AI agents, including: Revenue Operations (RevOps) leads, Customer Success managers, Sales Operations, Product managers, and Data-savvy executives in scaling tech companies.
3. Use Cases: Essential for automating complex, cross-functional processes. Specific scenarios: 1) Synchronizing deal stages across sales, support, and finance agents. 2) Automating weekly business performance digests from multiple data platforms. 3) Enforcing and scaling customer renewal save playbooks across the CS team. 4) Maintaining pipeline hygiene by identifying and reactivating stale deals.

Unique Advantages

1. Differentiation: Unlike static vector databases or simple chat memory, N71 offers a cascading, real-time knowledge graph. Competitors often provide passive memory; N71 actively models relationships and propagates updates (e.g., if a deal amount changes, all dependent forecasts update automatically), which its benchmark (0.628 cascade score) validates.
2. Key Innovation: The integration of a self-correcting knowledge graph with MCP for agent orchestration. This combination of a dynamic, context-aware "company brain" and a standardized protocol for agent access is its core technical innovation, moving beyond single-agent memory to multi-agent, system-aware intelligence.

Frequently Asked Questions (FAQ)

1. What is N71 AI used for? N71 AI is used to create a shared, real-time memory system for multiple AI agents, enabling them to work in concert on business processes like sales pipeline management, customer success automation, and data reporting without manual context switching.
2. How does N71 compare to other AI memory systems? N71 differentiates itself through its dynamic knowledge graph that updates cascading facts in real-time and its use of MCP to serve context to agents, as demonstrated by its leading scores (0.574 overall) in independent benchmarks for context accuracy and cascade updating.
3. What is MCP and how does N71 use it? MCP (Model Context Protocol) is a standard for tools to provide context to AI models. N71 uses MCP as a server, allowing any MCP-compatible AI client or agent to securely query and read from its always-updated knowledge graph, making the context universally accessible.
4. What kind of data sources can N71 connect to? N71 connects to operational tools typically used by knowledge workers, such as CRMs (e.g., Salesforce), payment platforms (e.g., Stripe), analytics suites (e.g., Mixpanel), and collaborative documents, creating a unified model without data migration.
5. Is N71 an autonomous AI agent? No, N71 is not an autonomous agent. It is an orchestration and context platform. It provides the shared memory and proactive workflow prompts ("Thoughts") that human-supervised AI agents use to execute coordinated, context-aware tasks.