Build AI Sales Intelligence Agent
This challenge tasks you with developing an advanced, agentic AI system. Your system will act as a 'Sales & Competitive Intelligence Unit,' leveraging a team of specialized agents to monitor market trends, analyze competitor strategies, and generate highly targeted sales pitches. The core of this system will be a CrewAI-orchestrated multi-agent framework, utilizing cutting-edge LLMs for reasoning and advanced communication protocols for seamless collaboration. The system must identify emerging opportunities, dissect competitor product launches or funding rounds, and synthesize this information into actionable sales strategies. Emphasis is placed on building agents capable of extended thinking and adaptive reasoning, allowing them to delve deep into complex market dynamics while remaining efficient. The integration of a RAG system for comprehensive data access and a simulated MCP for enterprise system connectivity will be crucial for real-world applicability.
What you are building
The core problem, expected build, and operating context for this challenge.
Build a role-based multi-agent system using CrewAI with GPT-5 and Claude Sonnet 4 for advanced sales intelligence and competitive analysis.
How work is evaluated
The evaluation will focus on the system's ability to accurately analyze market conditions, formulate coherent strategies, and generate persuasive sales pitches, while demonstrating effective agent collaboration and tool integration.
Challenge datasets
Public datasets, plus the private datasets you have access to.
What you should walk away with
Develop extended thinking pipelines with adaptive reasoning budgets using GPT-5.
Implement A2A protocol for secure, efficient inter-agent communication.
Integrate a RAG system for comprehensive competitive data access.
Design and orchestrate role-based agent teams using CrewAI.
Generate actionable sales strategies and dynamic, targeted sales pitches.
Reference links and supporting material
Sample data for 2 tasks
Challenge setup
The evaluation will focus on the system's ability to accurately analyze market conditions, formulate coherent strategies, and generate persuasive sales pitches, while demonstrating effective agent collaboration and to...
Challenge input
{'industry': 'string', 'competitor_name': 'string', 'focus_areas': ['string']}
Agent execution
No agent tool is listed for this challenge.
Evaluated output
{'report_title': 'string', 'executive_summary': 'string', 'sections': [{'heading': 'string', 'content': 'string', 'key_insights': ['string']}]}
- Ensures the Market Analysis Report contains executive summary, key sections, and insights.
- Verifies the Sales Pitch Generation output adheres to the specified format (email/script) and includes a su...
- MarketInsightDepth target: 8
- Python execution harness
Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.
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Configured tools
No tool records are attached.
Evaluation contract
- Ensures the Market Analysis Report contains executive summary, key sections, and insights.
- Verifies the Sales Pitch Generation output adheres to the specified format (email/script) and includes a subject/body/CTA.
Metrics
- MarketInsightDepth · Target 8
- PitchRelevanceToPersona · Target 9
- AgentCollaborationEffectiveness · Target 8
Workflow tasks
- Task 1
Input: {'industry': 'string', 'competitor_name': 'string', 'focus_areas': ['string']}
Output: {'report_title': 'string', 'executive_summary': 'string', 'sections': [{'heading': 'string', 'content': 'string', 'key_insights': ['string']}]}
Execution harness: Python
- Task 2
Input: {'market_analysis_report': 'json', 'target_persona': {'role': 'string', 'industry': 'string', 'pain_points': ['string']}}
Output: {'pitch_format': 'email|script', 'subject_line': 'string', 'body': 'string', 'call_to_action': 'string'}
Execution harness: Python
Recipe freeze marker
No recipe freeze time is recorded.