Building the intelligence layer for AI-native marketing teams

Lemonado is your marketing team's AI co-worker. Like a hire, it connects to your entire stack and does the work end-to-end: pulling data, building reports, optimizing accounts. It executes, it doesn't just report, so your people spend their attention on decisions instead of busywork.

You work with it three ways: talk to it in Chat, work alongside it in the Studio and Ads workspaces, or hand work off to it with Tasks.

You can wire ChatGPT or Claude up to a few of your marketing tools today, and people do. The catch is what you get back. Each connector pulls raw data from one platform in isolation, with no shared definitions, no client context, and no governance. Ask a real question across Google Ads, Meta, LinkedIn, GA4 and revenue and you get a different answer every time, or no answer at all.

Lemonado is the layer underneath. We blend every platform into one governed, query-ready dataset, keep persistent context per client and brand, and expose it to ChatGPT, Claude, Cursor, or n8n through a single MCP. The AI tool you already use stays, but the answers are now grounded in your actual marketing data, and consistent across the whole team.

Yes. With Studio you build dashboards and reports by describing them, on live data, with no manual pipelines, no paid connector per source, and no drag-and-drop widget building. Studio refreshes in real time, not on a cron.

Then the same AI co-worker works on top of it: monitoring accounts, optimizing them, and delivering the reports on a schedule.

No. It does the manual work so your people spend their attention on judgment, strategy, taste, and clients. It is additive: it joins the team you already have, and gets better the more you work with it, because it keeps your team's shared context in one place.

Over 3,000. Native connectors cover the core marketing stack: Google Ads, Meta Ads, LinkedIn Ads, TikTok, Pinterest, Snapchat, Microsoft Ads, YouTube, Google Analytics, Search Console, Google Sheets, Shopify, Stripe, HubSpot, Klaviyo, and Snowflake.

Beyond those, point Lemonado at any product with an API and it builds the connection itself, handling keys, auth, and setup. You can also upload CSVs straight into the same governed layer. See the full list on integrations.

Yes, and any AI tool that supports MCP, including Cursor and n8n. In Lemonado you click one button to create an MCP connection. Each connection is per-client, scoped, and read-only, so an outside AI tool can read your governed data but never write to your accounts.

MCP is included from the Automate plan up.

Every question runs as a real SQL query against your live data, with full source attribution. You can see exactly which rows the answer came from, trace the logic, and verify the numbers. Answers are explainable, not speculative.

Yes, and that is the point: Lemonado executes rather than just reporting. It optimizes accounts and rebalances budgets through the connections you have granted, inside the workspace you granted them in. Every task and agent run is visible in the app, so you can see exactly what it did and when.

External AI tools connected over MCP (ChatGPT, Claude, Cursor, n8n) can never write to your accounts. Those connections are read-only by design.

Lemonado is built by a Swedish company, data is hosted in the EU, and GDPR-grade handling is the default rather than an add-on. Your data is never used to train AI models, ours or our providers'.

Every company or client lives in its own scoped workspace, and one workspace can never read another's data. Connector access is scoped and revocable at any time, and external AI connections over MCP are read-only. Enterprise adds SSO, row-level permissions, and white labeling.

For our DPA or a security questionnaire, email security@lemonado.io.

Two ways. Start free with the $150 in credits we front you, for up to 10 days, no card required. Or book a demo and we'll walk your stack with you.