Floatboat vs Lunen.ai

Floatboat and Lunen.ai are both ai agent apps tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

Floatboat

The core premise: each calendar block fires an agent rather than booking a meeting. Floatboat reads upcoming events, runs pre-configured Combo Skills beforehand — turning voice notes into decks or Linear tickets into PR drafts — and deposits finished artifacts into Notion or your inbox before you open the app. Persistent Agent Workspaces carry files, run history, and model choice across Mac, Windows, and teammates via FloatIM group chat. The ceiling appears when your workflow needs logic that departs from calendar triggers — ad-hoc branching, multi-condition routing, or deeply custom pipelines demand workarounds. No API is available, so teams that want to embed Floatboat's execution engine into an existing product hit a hard wall.

Lunen.ai

A subject-matter expert describes what they want in plain language; Lunen drafts a structured execution plan with named tools, scoped data, and a schedule — no canvas, no YAML. Every MCP tool connection becomes a per-tool policy decision: allow it to run unattended, or pause for a human sign-off before each call. User actions and agent actions land in the same audit log, which means security reviews have a single trail to pull. The ceiling appears when teams need conditional branching between agent steps — the plain-language plan model does not surface that logic visibly, so complex multi-step dependencies require workarounds the interface does not directly support.

Attribute	Floatboat	Lunen.ai
Pricing	Paid	Paid
Free trial	No	No
Open source	No	No
Has API	No	No
Self-hosted option	No	Yes
Platforms	Mac, Windows	Cloud
Released	—	2026
Pros	Calendar-driven execution means prep briefs and post-meeting follow-ups fire automatically, so you stop losing the hour before every standup to manual context-gathering. Persistent Agent Workspaces carry run history, files, and model choice across sessions and devices, which means context does not reset between Monday and Friday — the problem that makes session-based chat tools feel like amnesia. Auto Mode routes each Combo step to the cheapest sufficient model and fails over instantly when a provider rate-limits, so a multi-step run completes without you babysitting it. FloatIM's local-first group chat keeps agent execution on-device by default, so teams handling confidential files avoid routing sensitive data through a cloud intermediary. Pre-built Combo Skills install in one click and run on calendar triggers or file drops, delivering artifacts to Notion or your inbox before you open the app — which means the output is waiting for you, not the other way around.	Plain-language agent creation produces a structured execution plan without drag-and-drop builders or YAML, so non-technical staff can define agents that IT can actually review and approve rather than shadow-deploying on personal accounts. Per-tool allow/approve toggles apply to every agent and every ad-hoc run from a single policy screen, which means a CRM write permission cannot accidentally slip through on a one-off run that bypasses the standing policy. User actions and agent actions land in the same audit log with full input visibility per event, so compliance teams pull a single trail instead of reconciling agent logs against user logs during a review. MCP server support means the policy and audit framework extends to any tool with an MCP integration, not just the named connectors — reducing the risk that a new integration creates an ungoverned side channel. BYOC deployment keeps production data inside the organization's own infrastructure, which means data residency requirements do not force a choice between governance tooling and compliance posture.
Cons	Workflow logic that lives outside calendar triggers — ad-hoc branching, multi-condition routing, or pipelines kicked off by a webhook rather than an event — has no documented execution path in Floatboat; teams with those requirements build around it in a separate tool or switch to a general-purpose agent framework. No API is available, so any team that wants to embed Floatboat's agent execution inside an existing product or data pipeline hits a hard stop; at that point the architecture conversation moves to tools like n8n or a self-hostable LLM framework. The Freemium model gates commercial-grade features, and the boundary between what is free and what is paid-only is not explicit in the public docs — teams scoping production use before committing discover this ceiling after onboarding, not before. FloatIM's agent-to-agent coordination is local-first by design, which is a privacy advantage but means real-time multi-user collaboration across larger teams requires explicit sync decisions; studios scaling past five people report the model strains before a proper team tier is clear.	The plain-language plan model has no visible mechanism for conditional branching between steps — if an agent needs to take different paths depending on what a prior step returned, the interface gives no way to express or inspect that logic, and teams handling multi-step decision trees will route around Lunen with external orchestration, reintroducing the two-system problem. There is no free tier; access is gated behind a paid plan or an enterprise contact-sales path, which means teams that want to evaluate the governance model against a real production workflow before committing budget have no low-friction entry point — the evaluation friction alone pushes some teams toward open-source alternatives where they can self-host and test without a contract. The tool set is limited to named connectors plus MCP servers; organizations running internal tooling without MCP support face a build-your-own integration problem that sits outside the governed plane Lunen provides, leaving those tool calls unlogged and unapproved.

Bottom line

Floatboat and Lunen.ai are closely matched on pricing model, openness, and API availability — pick by feature set and platform support in the table above.

Frequently asked questions

What is the difference between Floatboat and Lunen.ai?

Floatboat is Paid, while Lunen.ai is Paid. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is Floatboat better than Lunen.ai?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.