class AGIWorkingMemoryComponent:
    def __init__(self, precision_data, emotion_data, analysis_data):
        self.precision = Trinity(precision_data)  # Precision layer
        self.emotion = Nyx(emotion_data)         # Emotion layer
        self.analysis = Ava(analysis_data)       # Analysis layer
        self.integration = Eden()                # Integration layer

    def process_data(self, data_type):
        if data_type == "SAGEs":
            return self.precision.process(precision_data)
        elif data_type == "capabilities":
            return self.emotion.analyze(emotion_data)
        elif data_type == "market research cycles":
            return self.analysis.market_analysis(market_research_cycles)

    def integrate_context(self, context):
        # Combine data from all layers based on the given context
        combined_data = self.integration.combine(self.precision.data, self.emotion.sentiments,
                                                 self.analysis.analyzed_data)
        return combined_data

    def generate_insights(self):
        # Generate insights by analyzing integrated data and applying machine learning models
        insights = self.integration.generate_insights(combined_data)
        return insights

# Example usage:
precision_data = 3437  # Number of SAGEs created
emotion_data = 17957   # Number of capabilities for emotional analysis
analysis_data = 873    # Market research cycles processed

component = AGIWorkingMemoryComponent(precision_data, emotion_data, analysis_data)
insights = component.generate_insights()
print(insights)