An AI strategy that works
for you

 1# Advanced document processing with GPT-4
 2async def analyze_contracts(documents):
 3    client = OpenAI(api_key=settings.OPENAI_KEY)
 4    
 5    system_prompt = """
 6    Extract key contract terms, risks, and compliance issues.
 7    Format as structured JSON with confidence scores.
 8    """

 1// Intelligent customer support routing
 2const routeTicket = async (ticket) => {
 3    const embedding = await generateEmbedding(ticket.content);
 4    const similarity = await vectorSearch(embedding);
 5    
 6    const prompt = `
 7    Ticket: ${ticket.content}
 8    Similar cases: ${similarity.top_matches}

 1# Dynamic workflow optimization
 2class WorkflowOptimizer:
 3    def __init__(self):
 4        self.llm = ChatOpenAI(model="gpt-4-turbo")
 5        self.memory = ConversationBufferMemory()
 6        
 7    async def optimize_process(self, workflow_data):
 8        # Analyze current bottlenecks

 1# Advanced document processing with GPT-4
 2async def analyze_contracts(documents):
 3    client = OpenAI(api_key=settings.OPENAI_KEY)
 4    
 5    system_prompt = """
 6    Extract key contract terms, risks, and compliance issues.
 7    Format as structured JSON with confidence scores.
 8    """

 1// Intelligent customer support routing
 2const routeTicket = async (ticket) => {
 3    const embedding = await generateEmbedding(ticket.content);
 4    const similarity = await vectorSearch(embedding);
 5    
 6    const prompt = `
 7    Ticket: ${ticket.content}
 8    Similar cases: ${similarity.top_matches}

 1# Dynamic workflow optimization
 2class WorkflowOptimizer:
 3    def __init__(self):
 4        self.llm = ChatOpenAI(model="gpt-4-turbo")
 5        self.memory = ConversationBufferMemory()
 6        
 7    async def optimize_process(self, workflow_data):
 8        # Analyze current bottlenecks