Draft personalized outreach for leads
Run an AI SDR that works through your lead list, researches each company on the web, drafts personalized cold emails grounded in your product knowledge, and switches on cold email automation when you are ready to send.
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Running on a set time schedule (e.g. once daily), an AI agent works through a lead list in [lead management system/CRM] and picks up each contact that has not yet been emailed, runs live web research on their company using [web research tool], and pulls product positioning and proof points from knowledge files in [knowledge file storage] to draft a tailored subject and message guided by the rep's pitch direction. It writes the draft back to the lead record in [lead management system/CRM], sends it through [email sending tool, e.g. Gmail, Outlook, SendGrid] and marks the lead in [lead management system/CRM] when sending is enabled, and skips any lead missing an email, company, or website with a clear note in [lead management system/CRM] explaining why. Each scheduled run should only process leads not yet marked as sent, so newly added leads are handled automatically on the next run.
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Problem
Sales reps manually research each lead's company, dig through positioning and proof points, and write a tailored email one prospect at a time. This is slow, inconsistent across reps, and forces a tradeoff between personalization and the volume needed to keep the pipeline full.
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Solution
On a set schedule, an AI agent picks up each lead not yet emailed from the lead list, runs live web research on their company, and pulls product positioning and proof points from uploaded knowledge files to draft a tailored subject and message guided by the rep's pitch direction. It writes the draft back to the lead record, sends it by email and marks the lead when sending is enabled, and skips any lead missing an email, company, or website with a note explaining why.
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Impact
Reps reach every prospect on their list with researched, on message outreach, so personalization no longer comes at the cost of pipeline volume.
Benefits
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Increased outreach volume
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Higher reply rates
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Faster prospect research
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Consistent rep messaging
Who is this for?
Success stories
Adapt at speed with visual-first automation and AI
Make drives efficiencies, solves problems, and speeds innovation by breaking down silos across your business.
Similar use cases
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Research accounts before outreach
On a set schedule, an AI agent works through the list of companies in the company database, picks up any that have not been researched yet, and runs live web research to gather the specific details the team asks for, judging what is relevant for each company as it goes. It compiles the findings into a consistently structured brief, creates a document for it, and writes the link back to the company record.
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Qualify inbound leads against your ICP
When a new lead is submitted through the intake form, an AI agent researches the company using live web search and weighs what it finds against the Ideal Customer Profile and disqualifiers pulled from uploaded knowledge files. It judges fit for each lead in context, then logs an ICP match score and a short evidence based reason to a spreadsheet.