Lunen.ai

Lunen.ai

Lunen.ai is an enterprise agent orchestration platform that lets teams build, schedule, and govern AI agents in plain language while enforcing permissions, policy approvals, and comprehensive audit trails so AI can pass security reviews.

Lunen.ai is ai tools software teams evaluate for content & marketing. Use this page to review pricing, integration signals, and the best alternatives before you commit.

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#417 in AI Agents (417 tools)
Just launched
Data reviewed Jul 20, 2026

Quick Overview

Best for: Content & Marketing

What it does

AI Tools software for decision-makers comparing workflow fit and alternatives.

Best fit

Content & Marketing

Pricing snapshot

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Lunen.ai

Lunen.ai is an enterprise-focused agent orchestration platform designed to let subject-matter experts describe AI agents in plain language while simultaneously scoping data, setting permissions, and logging actions for security reviews. It aims to unify the builder and governance paths so teams can ship AI workflows that meet enterprise security and audit requirements. The product targets teams in enterprises (marketing, legal, media, etc.) that need scheduled or ad-hoc agents integrated with existing tools and governed through a single control plane.

Build AI agents your whole team can run, and control Discussion | Link

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Key Features

Plain-language agent authoring

Subject-matter experts type what they want in plain language and Lunen drafts a structured execution plan with named tools, scoped data, and a schedule ("Describe the agent. Watch the plan write itself").

Policy & approval controls

Every MCP tool becomes a policy decision: allow unattended runs or require human approval before each call; the same toggles cover agents and ad-hoc runs ("AllowRuns unattended" / "Approve Pauses for a human OK on every call").

Audit trail and event logging

User actions and agent actions roll up in the same audit log with event details including actor, model run, data touched, and approvals; logs are exportable on demand ("Everything a security review needs, exported on demand").

Tool integrations and MCP support

Connectors shown include HubSpot, Slack and other MCP servers; tools are referenced by name in execution steps (examples: HubSpot · contacts, Slack · #marketing-leads, Remote MCP com.hubspot/remote-mcp-server).

Scheduled and ad-hoc runs

Agents can be scheduled to run (example: Daily · runs at 7:30 AM) or executed ad-hoc with the same governance and audit controls.

Execution blueprint & step-level plan

Lunen drafts a structured execution plan with discrete steps (Tool, Reasoning, Notify) that can be reviewed before running.

Pricing

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Use Cases

Marketing lead scoring and notifications

An agent pulls yesterday's new leads from HubSpot, scores each lead on fit and intent, drafts a one-line 'why call' note, and posts a ranked list to Slack (example plan: Pull leads → Score → Read prior engagements → Rank → Notify).

RevOps digest and objection clustering

An agent pulls closed-lost deals and associated notes, clusters objections, drafts a digest, and posts to a RevOps Slack channel (example plan steps shown for HubSpot deals and engagements).

Cross-team scheduled agents

Multiple teams (Marketing, Legal, Media) can run distinct agents overnight and receive tailored morning outputs, enabling scheduled automation with governance and approvals.

Integrations

HubSpot

Used in examples to pull contacts, deals, engagements and to create or update CRM objects (examples: HubSpot · contacts · last 24h; hubspot:crm_create_object).

Slack

Used to post notifications and ranked lists to channels (examples: Slack · #marketing-leads; Slack · #revops).

Atlassian

Listed among supported tools for agent integrations on the site.

BigQuery / Google

Listed among supported tools for agent integrations on the site (BigQuery, Google).

Any MCP server / Remote MCP

Supports integration via MCP servers (example: Remote MCP com.hubspot/remote-mcp-server) so enterprise tooling can be used under governance controls.

Benefits

Combines agent building and governance in a single flow so teams can deliver AI that passes security reviews.
Fine-grained policy controls (allow vs require approval) reduce risk while enabling automation.
Comprehensive audit logs and exportable event data provide evidence required for compliance and incident review.
Plain-language authoring lowers the barrier for subject-matter experts to create agents without engineering or YAML.

Limitations

Currently available to a limited group of design partners / early access customers ("We're working directly with a small group of design partners to shape Lunen").
Requires configuring MCP tools and explicit permissions/policies before agents can run unattended (UI shows tools and '0/5 configured' permissions).

Frequently Asked Questions

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Getting Started

  1. 1 Request early access / Contact sales to join the design partner program ("Get early access", "Contact sales").
  2. 2 Describe the agent in plain language in the Lunen UI and review the drafted execution plan.
  3. 3 Scope data and set policy/permissions for each MCP tool used, choose unattended runs or require approvals.
  4. 4 Save and run the agent (schedule or ad-hoc) and review actions in the audit log.

Support

Contact sales

Request early access or schedule a call via the Contact sales flow referenced on the site ("Get early access", "Contact sales").

Company site / heritage

REDspace background and enterprise platform experience available via redspace.com.

API

Available: No

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