Outreach that feels truly researched. Handled by AI agents.

AI agents pull leads' context from websites, LinkedIn, past calls, and your CRM to help you score better and send outreach hard to ignore.

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Case study
Case study
& 20,000+ other sales teams run their entire outbound in lemlist
use cases

5 data sources. 1 platform. 0 manual research.

Each AI agent reads a different source, straight in lemlist, giving you data for better scoring and messaging.

Jérémy Grandillon

“Sales reps no longer need a GTM engineer to enrich their sequences. With lemlist’s Agentic Enrichment, I can pull relevant data from websites or LinkedIn and use it instantly to personalize my outreach. No external tools. No complex workflows. No waiting on someone technical.”

Jérémy GrandillonCEO · TC9
how to

It only takes 3 steps to get the unique leads’ context.

Step 1

Create a field that thinks for you

Add a new column to your leads table as a source of information that agents will find and organize for you in the format you request.

Step 2

Define what you’d like to know and the format

Choose the sources of information you want (URL, LinkedIn, past calls, or CRM) and describe the outcome you want returned as a variable.

Step 3

Instantly get leads’ context you can act on

The agent runs across all your leads and turns raw data into clear, structured insights, returned as ready-to-use variables you can plug into your sequence.

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resources

How to use agentic enrichment to extract data and personalize outreach

Video

Agentic Enrichment: Website Scraper

with Jeremy, CEO at TC9

Watch on YouTube

Video

Agentic Enrichment: LinkedIn Connector

with Rémi, GTM at lemlist

Watch on YouTube

Frequently Asked Questions

AI agents are automated “research assistants” that analyze data for you at scale.

In practice, you define what you care about (for example: “find leads who recently changed jobs” or “extract a relevant insight for outreach”), and the agent goes through your leads, pulls data from sources like LinkedIn, websites, CRM, or past calls, and turns it into structured, usable outputs.

Most AI tools help you generate text or collect data. This goes further by turning raw data into structured insights you can directly use in your workflow.

Instead of running prompts one by one or combining multiple tools, you set your logic once, and the agent applies it across all your leads automatically.

Agents can analyze multiple data sources at once, including websites, LinkedIn profiles, CRM data (HubSpot, Salesforce), and past call transcripts.

This allows them to build a more complete understanding of each lead, not just isolated data points, but actual context you can act on.

The output is structured data you can immediately use in your workflow.

This can include things like lead scores, segmentation tags, intent signals, key insights, or personalized message variables, all formatted so they can be plugged directly into your outreach or filtering logic.

Very little. You don’t need to build workflows or write complex prompts.

You simply describe the outcome you want in plain language, and the agent translates that into logic that runs across your entire lead list.

Yes, personalization is just one use case.

You can also use AI agents to qualify leads, prioritize outreach, detect buying signals, segment audiences, and re-engage existing opportunities based on real context.

By removing manual research, you don’t just save time, you make better decisions.

Instead of sending more messages, you focus on the right leads at the right time with the right context, which typically leads to higher reply rates and more meaningful conversations.