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AI-Powered Meeting Preparation Agent
"Your senior AEs are probably spending 4-5 hours a week just preparing for meetings—time they could be spending actually selling. We help companies cut that to 30 minutes while their reps actually show up better prepared."
The Problem
Sales reps spend 4-5 hours per week researching prospects before meetings—time that could be spent selling. Preparation quality varies wildly: senior reps do thorough research, while junior reps often walk in underprepared. The information needed is scattered across CRM, email threads, news sources, and LinkedIn. When preparation is poor, it shows: deals stall, prospects disengage, and competitive positioning suffers. The problem compounds in complex B2B sales where understanding stakeholder dynamics and recent company events is critical to earning trust.
Current State
Reps manually search LinkedIn, company websites, news, and CRM before meetings. Quality depends entirely on individual discipline and experience. Some reps spend 45 minutes preparing for each meeting, others spend 5. Meeting notes from previous interactions are buried in CRM activity logs or personal notebooks. There is no systematic way to surface what matters most for each specific meeting context.
GenAI Solution
AI reads: CRM data, email threads, calendar events, company news, LinkedIn profiles, previous meeting notes, deal history. AI generates: 1-2 page briefing with executive summary, key talking points, potential objections, suggested questions, stakeholder changes, and recent company events relevant to the deal. AI decides: Which information is most relevant for the specific meeting context, prioritizing and synthesizing rather than dumping raw data. Optional audio summary for commute listening.
Key Differentiator
Traditional automation can pull data from systems, but GenAI synthesizes and prioritizes information into actionable narratives. It understands which news is relevant to the specific deal, identifies patterns in communication tone, and generates personalized talking points—tasks requiring language understanding beyond rules-based systems.
Example Workflow
- 1 Calendar event with customer triggers automated preparation workflow
- 2 AI retrieves CRM data, scans email threads for commitments and concerns, pulls recent company news, identifies stakeholder changes
- 3 AI generates 1-2 page briefing with executive summary, key talking points, potential objections, and suggested questions
- 4 Optional: generates audio summary for commute listening
- 5 Rep reviews briefing, adds personal relationship notes, adjusts strategy
- 6 Ready-to-use meeting preparation document with key insights highlighted
Prerequisites
- CRM with opportunity data
- Calendar integration
- Company database access (LinkedIn Sales Nav or similar)
- Internal knowledge base or product docs
Red Flags
- Very transactional, high-volume sales (no real meeting prep needed)
- Company has dedicated sales research/intelligence function already staffed
- CRM data is a complete mess with no investment planned to fix it
- Average deal size under €5K (prep investment doesn't justify)
- Sales team under 5 people (manual process is manageable)
Complexity Drivers
CRM integration depth, number of data sources to connect (email, LinkedIn, news), data quality in existing systems, multi-language requirements for European markets
Risk Factors
Poor CRM data quality undermines briefing accuracy; low adoption if briefings aren't actionable; integration delays with legacy systems
Value Metrics
Hours spent on meeting preparation; meeting effectiveness
4-5 hours/week per rep on manual research; inconsistent preparation quality
30 minutes/week with AI-generated briefings; consistently high preparation quality
Industry Perspectives
Specific pain points, solutions, and regulatory factors for 6 industries.
C-Suite Relevance
Key Metrics
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