AI-Powered Sales Assistant for Consortium Financing
My Consortium
We help automotive and real estate consortia convert more qualified leads using AWS-native conversational AI grounded in verified internal documents.
Private preview in progress
🔹 THE PROBLEM
Complex Products. Confused Customers. Lost Sales.
Consortium sales are complex, long, and often manual.
Customers struggle to understand eligibility, pricing, and rules — leading to lost conversions and frustrated sales teams.Traditional CRMs and lead tools don’t provide the real-time, contextual guidance that structured sales require.
🔹 OUR SOLUTION
Conversational AI for Consortium Sales
MyConsortium is an AI-powered sales assistant that:
• Answers customer questions using official product and rule documentation
• Qualifies and guides leads through complex offerings
• Reduces sales team workload while improving conversion ratesBuilt with AWS for security, scalability, and responsible AI.
🔹 Use Cases
🚗 Automotive &
🏠 Real Estate Consortium Sales
| Automotive Consortia | Real Estate Consortia |
|---|---|
| 🟦 Explain plans and contribution rules 🟦 Clarify pricing and eligibility 🟦 Support dealer networks | 🟦 Guide buyers through complex offers 🟦 Explain financing and timelines 🟦 Qualify potential investors |
Outcome
✔ Higher lead conversion
✔ Reduced agent load
✔ Faster customer decisions
✔ Consistent compliance
🔹 HOW IT WORKS
TECH OVERVIEW
1. Customer asks a question via chat or form
2. Relevant internal documentation is retrieved using vector search
3. AWS foundation models create source-grounded responses
4. Sales team gets qualified leads + insights
What problem does this solve for me?
Lead-to-Recommendation Conversational Flow
The conversational flow above is powered by a retrieval-augmented AI architecture, described in next section
Lead-to-Recommendation Conversational Flow
This subflow is designed to automatically engage and qualify leads coming from Meta Ads, Google Ads, or website forms, and guide them toward a personalized consortium recommendation.1. Lead Reception
When a lead is received, the conversational agent initiates contact using the context from the ad or form (e.g. consortium type, campaign, intent).2. Identity & Data Validation
The assistant confirms key customer details (such as CPF and date of birth) to ensure accuracy before proceeding.
If corrections are needed, the flow loops safely until valid data is provided.3. Personalized Simulation Preparation
Once validated, the system prepares a tailored simulation based on the customer’s profile, preferences, and available products.4. Value-Oriented Recommendation
The assistant presents relevant benefits (e.g. reduced installments, flexible plans), focusing on clarity and decision support — not pressure.5. Decision HandlingIf the lead confirms interest, the process continues fully online.If the lead needs more time, the system provides additional information and pauses respectfully.6. Automated Follow-up & Human Fallback
If there is no response, a timed follow-up is triggered.
When automation cannot proceed (e.g. validation issues), the conversation is seamlessly handed over to a human agent.Outcome:
Higher lead conversion, faster response time, and consistent recommendations — while keeping humans in control when needed.
Use Cases
🔹 How the Conversational AI Flow Works
Conversational AI for Consortium Sales
The following describes, at a high level, how we structure a Retrieval-Augmented Generation (RAG) flow for consortium sales use cases.
Brief Description of the Flow
A. Raw Data Sources →The process begins by collecting approved knowledge sources such as internal documents, PDFs, web content, and product or program materials relevant to consortium sales and partners.B. Information Extraction →Key structured information is extracted from these sources, including eligibility rules, product specifications, policies, and frequently asked questions.C. Chunking →The extracted content is segmented into smaller, meaningful text chunks to improve retrieval precision and response relevance.D. Embedding →Each content chunk is converted into vector embeddings — numerical representations that capture semantic meaning and enable efficient similarity search.Retrieval-Augmented Generation (RAG) Flow
1. Query → EmbeddingWhen a user submits a question, the system converts the query into a vector embedding.2. Query Embedding → Vector DatabaseThe query embedding is used to search a vector database for the most semantically relevant content.3. Relevant Data RetrievalThe system retrieves the best-matching chunks based on similarity and relevance.4. Retrieved Data → LLMThe retrieved knowledge is passed to the Large Language Model together with the user’s query, providing grounded context.5. Response GenerationThe LLM generates an accurate, context-aligned response based on both retrieved data and reasoning capabilities.Why This Matters for Consortium Sales• Ensures responses are grounded in validated, approved content
• Reduces misinformation and hallucinations
• Supports controlled pilots before scaling to institutional use
WHY AWS
We rely on AWS for core infrastructure:
• Amazon Bedrock for managed foundation models
• Secure document storage and retrieval
• Scalable, compliant cloud architecture
• Cost-effective AI inference with monitoring and controlAWS enables rapid prototyping and secure production deployment.
Use Cases
🔹 Request a Pilot / Demo
Explore a Pilot or Discuss Your Use Case
We help consortium sellers and financial organizations validate risk, fraud, and operational decisioning through small, cloud-based pilots before scaling to production environments.
This solution is designed to help you:• Structure and validate digital sales and eligibility flows
• Reduce fraud and operational risk in consortium origination
• Pilot decisioning logic without heavy IT investment
• Prepare your operation for future institutional partnerships
🔹 Request a Pilot / Demo
🔹 What Happens After You Submit
After receiving your request:• We review your context and objectives
• We schedule a short discovery call
• If relevant, we define a pilot scope, timeline, and success criteria
We reply within 24 hours.
🔹 Contat Us
Let’s Build the Right Solution Together
Have a question, idea, or partnership in mind?
Send us a message and we’ll get back to you shortly.
🔹 What Happens After You Submit
After receiving your request:• We review your message
• We evaluate how we can help
• We get back to you shortly
We reply within 24 hours.