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.
Start for free20,000+ sales teams* use lemlist to book meetings
*Not for show. They're running sequences right now.
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.
Scrape web pages
What AI agent does:
Analyzes key pages (homepage, pricing, product) to understand how the company positions itself, who it’s for, and what’s the main value prop.
Use cases:
Quickly qualify ICP fit, spot relevant signals (like hiring or launches), craft a tailored pitch angle, and personalize messaging based on their tech stack.
Research LinkedIn profiles
What AI agent does:
Analyzes LinkedIn profiles to understand role history, seniority, and career trajectory, surfacing the signals that make a message feel truly personal.
Use cases:
Find genuine common ground for icebreakers, spot signals such as recent promotions or job changes, qualify decision-maker fit, and prioritize leads most likely to engage.
Go through past calls
What AI agent does:
Reviews recorded Claap meetings to understand what was actually said. Resurface objections, intent signals, and key context from past conversations.
Use cases:
Re-engage warm opportunities, address real objections head-on, time your follow-ups to buying signals, and add personal context to make your outreach more relevant.
Dig into CRM
What AI agent does:
Reads your Salesforce & HubSpot CRM with understanding, grasping deal context, past interactions, and why opportunities moved or stalled.
Use cases:
Find genuine common ground for icebreakers, spot signals such as recent promotions or job changes, qualify decision-maker fit, and prioritize leads most likely to engage.
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 Grandillon
CEO at TC9
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.
How to use agentic enrichment to extract data and personalize outreach
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.
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.
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.
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.
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.
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.
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.
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.