Qualify inbound leads against your ICP

Automate inbound lead qualification by researching each company on the web, weighing it against your ICP with AI lead scoring, and logging a fit score with an evidence based reason.

Useful for
Sales development reps, account executives, and revenue leaders who triage inbound leads and want to prioritize outreach by fit without doing manual research.

Ready to use

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When a new lead is submitted through [intake form tool, web form], an AI agent researches the company using [web search tool] and weighs what it finds against the Ideal Customer Profile and disqualifiers pulled from [knowledge file storage]. It judges fit for each lead in context, then logs an ICP match score and a short evidence based reason to [spreadsheet tool, e.g. Google Sheets, Excel].

Guided by AI

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Start with an app-agnostic prompt, then let Maia guide you to the right apps and workflow.

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visual-first automation and AI

Make drives efficiencies, solves problems, and speeds innovation by breaking down silos across your business.

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Problem

Sales reps manually research each inbound lead, visiting company websites and searching the web to judge how well the company fits the Ideal Customer Profile. This is slow and subjective, so strong leads sit unqualified while reps spend time on prospects that were never a good match.

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Solution

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.

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Impact

Every inbound lead arrives scored and explained against your Ideal Customer Profile, letting reps focus their time on the prospects most likely to convert.

Benefits 

Who is this for? 

Sales development reps, account executives, and revenue leaders who triage inbound leads and want to prioritize outreach by fit without doing manual research.

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 

Find inspiration by the type of content that fits your goals.

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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.

Research accounts before outreach

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Draft personalized outreach for leads

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.

Draft personalized outreach for leads