Building an Intelligent Market

Building an Intelligent Market Monitoring Agent

Problem

Businesses rely on manual competitor analysis, which is slow and lacks historical tracking.

Solution

We built an AI agent that continuously monitors competitors and generates strategic insights using machine learning and NLP.

How Memory Works

Memory is implemented using a knowledge graph + embeddings, allowing:

• Relationship tracking (company → product → hiring)
• Context-aware insights
• Long-term learning

Code Snippet

competitor_data = {
    "company": "X",
    "feature": "AI chatbot"
}

def analyze(data):
    return f"{data['company']} launched {data['feature']}"

print(analyze(competitor_data))

Example

When a competitor launches a chatbot and hires NLP engineers, the agent connects both events and suggests:
👉 “Competitor focusing on conversational AI.”