Which HubSpot data does the AI employee use?

Deals, pipeline stages, contacts, and activities. He shows forecasted revenue based on your actual data, without you building dashboards.

Does he score leads automatically?

Yes. He scores leads by engagement and buying signals and shows you the most promising ones first.

Does he flag stalling deals?

He detects deals stuck too long in a stage or missing follow-ups and flags them before they go cold.

All integrations

HubSpot/CRM

Pipeline and deals in view

Your AI employee knows your HubSpot pipeline. He tracks deals, scores leads, and flags anything that stalls.

Book a demo

01 Problem

Problem

Why this matters.

Sales teams don't like maintaining CRM data. Deals get stuck in the wrong stage, follow-ups are forgotten, pipeline forecasts are never accurate. Your AI employee reads the actual HubSpot data and tells you which deals need attention. No dashboard, no filters, just ask.

02 Capabilities

Capabilities/ 4 features

What he can do with HubSpot. Concrete tasks your employee handles with HubSpot. Every day, without reminders.

HubSpot

Pipeline overviewDeal stages, conversion rates, forecasted revenue. Based on your actual data.

Lead scoringScores leads automatically by engagement and buying signals. Best ones first.

Activity trackingEmail opens, meeting bookings, website visits from your leads. All in one place.

Sales reportsPipeline velocity, win rate, forecasted close. Generated automatically.

03 Examples

Examples/ 2 examples

See it in action. Real conversations between you and your AI employee. This is how he works with HubSpot.

How does the pipeline look?

Pipeline value: 234k euros across 28 deals. 12 in Discovery, 9 in Proposal, 7 in Negotiation. Expected close this month: 67k euros (at historical win rate of 34%).

Which deals need attention?

3 deals stalling: 1) Muller GmbH (12k euros), no contact in 14 days. 2) Schmidt AG (28k euros), proposal open for 21 days. 3) Weber KG (8k euros), decision maker hasn't opened last 3 emails.

04 Onboarding

Onboarding

We set everything up. You get a personal onboarding. We connect HubSpot and configure everything for you.

Step 1

Book a demo

Show us your tools and goals. We show you what your employee can do.

Step 2

We connect

Our team sets up the integrations and configures everything to match your setup.

Step 3

Start

Your employee is ready. You ask, he answers. From day one.

05 Related

Works together. Tools that many HubSpot customers use together. Your employee connects the data.

06 Security

Who's behind it

Behind is a small team from Hamburg. Fewer than ten people building tailor-made AI employees for your store.

07 Pricing

Cheaper than any agency. We'll show you in 30 minutes how Neo takes over your store. Tailored to your tools, your data, your store.

Get started

Book a demo

No contract. We'll get back to you within 24 hours.

Neo, your in-house AI employee

All integrations included

Tailored to your store

German support

08 FAQ

FAQ/ 3 questions

Frequently asked questions about HubSpot

All integrations

HubSpot/CRM

Pipeline and deals in view

Your AI employee knows your HubSpot pipeline. He tracks deals, scores leads, and flags anything that stalls.

Book a demo

01 Problem

Problem

Why this matters.

02 Capabilities

Capabilities/ 4 features

What he can do with HubSpot. Concrete tasks your employee handles with HubSpot. Every day, without reminders.

HubSpot

Pipeline overviewDeal stages, conversion rates, forecasted revenue. Based on your actual data.

Lead scoringScores leads automatically by engagement and buying signals. Best ones first.

Activity trackingEmail opens, meeting bookings, website visits from your leads. All in one place.

Sales reportsPipeline velocity, win rate, forecasted close. Generated automatically.

03 Examples

Examples/ 2 examples

See it in action. Real conversations between you and your AI employee. This is how he works with HubSpot.

How does the pipeline look?

Pipeline value: 234k euros across 28 deals. 12 in Discovery, 9 in Proposal, 7 in Negotiation. Expected close this month: 67k euros (at historical win rate of 34%).

Which deals need attention?

3 deals stalling: 1) Muller GmbH (12k euros), no contact in 14 days. 2) Schmidt AG (28k euros), proposal open for 21 days. 3) Weber KG (8k euros), decision maker hasn't opened last 3 emails.

04 Onboarding

Onboarding