N71
N71 is a “company brain” that gives AI agents shared memory and proactive context by connecting your systems through a unified knowledge layer and retrieval stack, validated by published benchmark results.
https://n71.ai/?ref=producthunt
Product Information
Updated:Jul 2, 2026
What is N71
N71 is an AI intelligence platform positioned as the memory and context layer for AI agents—designed to help organizations retain knowledge, connect fragmented tools, and surface accurate insights quickly. Marketed as “the company brain that thinks ahead,” it focuses on turning scattered company information into a unified, usable context so that different AI tools and agents don’t “forget” when a session ends and can work from the same source of truth. N71 also emphasizes measurement and transparency, publishing benchmark outcomes (including failures) to substantiate its claims about memory performance.
Key Features of N71
N71 is a “company brain” (memory + context layer) for AI agents that connects to your existing systems and builds a unified knowledge graph with a retrieval/ranking layer so agents can surface accurate, up-to-date insights. It emphasizes measurable performance via published benchmarks (including failure cases) and supports rapid onboarding (“surface your first Thought in minutes”), with integrations (including MCP-based) designed to let multiple tools/agents share one consistent organizational context and handle changing facts through dependency-aware updates.
Unified knowledge graph memory: Creates a single, shared organizational context (“company brain”) by representing company knowledge in a unified knowledge graph so AI agents can reason over connected facts instead of isolated chat histories.
Hybrid retrieval + ranking layer: Production-grade information retrieval designed to surface accurate company insights, leveraging retrieval and ranking techniques (including vector databases/embeddings) to find the best supporting context for agent responses.
Change-aware fact propagation (Cascade): When a fact changes, dependent facts can update accordingly—aiming to reduce stale downstream knowledge and keep derived statements consistent with source-of-truth updates.
Absence awareness: Tracks what the system no longer knows (or what is no longer true), helping prevent agents from confidently using outdated or invalidated information.
System connectors + fast time-to-value: Designed to connect your internal systems and surface useful outputs quickly (“first Thought in minutes”), reducing the friction of deploying shared memory across tools.
Benchmark-driven transparency (MEME Benchmark): Publishes benchmark results and failures, including a downloadable evaluation suite (100 episodes, 1,188 questions) to validate memory performance claims.
Use Cases of N71
Customer support & service operations knowledge brain: Unify product docs, known issues, incident histories, and internal runbooks so support agents and AI assistants can retrieve the most current troubleshooting steps and avoid outdated guidance.
Enterprise search across siloed tools: Connect wikis, tickets, CRM notes, and engineering docs into one context layer so employees and agents can ask questions and get grounded answers with traceable, ranked context.
Sales & account intelligence: Aggregate account plans, meeting notes, emails/CRM fields, and product usage signals so AI agents can generate current account summaries and next steps that update as facts change.
Engineering & incident retrospectives: Maintain a living graph of services, owners, incidents, and mitigations; when ownership or architecture changes, dependent operational knowledge can cascade updates to reduce stale runbooks.
Multi-agent workflow coordination: Provide a shared memory/context substrate for multiple AI tools and agents so they can “talk to each other” via consistent facts, rather than each tool forgetting context after a session.
Pros
Benchmark-driven transparency with published results (and failures) plus downloadable evaluation questions for validation.
Strong focus on keeping knowledge current via change-aware updates (Cascade) and awareness of invalidated knowledge (Absence).
Built for real-world agent deployments: unified knowledge graph plus retrieval/ranking layer and integrations to connect enterprise systems.
Cons
Integration and knowledge-graph modeling can require meaningful setup and ongoing data governance to be effective in complex organizations.
Performance claims are benchmark-based; real-world outcomes may vary depending on connector coverage, data quality, and retrieval/ranking tuning.
As a specialized memory/context layer, teams may still need additional tooling for orchestration, UI, and end-to-end agent workflows.
How to Use N71
1) Go to N71: Open https://n71.ai/ ("N71 — The company brain that thinks ahead").
2) Start the signup flow: Click "Get Started" and proceed to the signup page at https://n71.ai/auth?mode=signup.
3) Connect your company systems (create a shared context): Connect the tools/systems your team already uses so N71 can act as a shared context layer ("Give all your AI agents one shared context" / "Connect your systems").
4) Enable MCP access for your agents/tools: Set up MCP access so your context can follow you into different agents/tools (the sources mention MCP access from Claude, ChatGPT, and Cursor).
5) Create your first "Thought": After connecting systems, generate/surface your first "Thought" (the site claims you can do this "in minutes").
6) Use provenance-backed answers: When N71 provides outputs, use its "Full provenance" capability so answers are cited to their sources.
7) Monitor the proactive feed for changes: Use the proactive feed to see what changed before you ask ("what changed, surfaced before you ask").
8) Rely on cascade updates when facts change: When underlying facts are updated in connected systems, use N71’s cascade behavior so dependent facts update accordingly ("Cascade — when a fact changes, dependent facts update").
9) Validate performance claims via benchmarks (optional): Review N71’s published benchmark results and methodology at https://n71.ai/benchmarks (MEME Benchmark June 12–16, 2026; includes downloadable questions for validation).
10) Scale to team usage and deployment needs (optional): Choose an operating model that matches your organization (team seats, annual commitment/managed option, or perimeter deployments including air-gapped/jurisdiction-bound tiers as referenced in the sources).
N71 FAQs
N71 is positioned as “the company brain that thinks ahead,” intended to give a company shared context by connecting its systems and surfacing insights (“Thoughts”) quickly.
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