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Sales Data Navigator for CRM & Marketing Insights

Empower your sales and marketing teams with instant, self-serve access to insights from CRM systems and marketing data—across both structured and unstructured sources. The Sales Data Navigator uses an AI agent to interpret natural language questions, select relevant data sources, and generate answers by translating user input into accurate SQL queries or retrieving documents using a RAG model. This AWS-based solution eliminates delays from data specialists, enables independent access to CRM insights, and delivers results in clear, business-friendly formats.

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About

Built with the power of Amazon Bedrock Agents, Adastra delivers a conversational AI agent that simplifies access to CRM and Marketing insights. By understanding natural language, the AI agent identifies the appropriate data sources—whether CRM databases or document repositories—and orchestrates the full workflow from data retrieval to insight delivery. The solution combines SQL translation for structured CRM queries and a RAG (retrieval-augmented generation) pipeline for unstructured documents.

Activities

Build and configure an AI agent that supports natural language interaction.

Connect the agent to CRM systems and marketing data sources.

Develop SQL translation capabilities to query structured CRM data.

Implement RAG model integration for unstructured data such as sales docs or briefs.

Create orchestration logic to select sources and execute queries.

Deliver a business-facing interface for query input and results.

Test for accuracy and usability across real-world marketing scenarios.

Provide documentation, onboarding, and knowledge transfer.

Deliverables

Fully functional AI agent integrated with CRM and marketing systems.

SQL translator for structured CRM database queries.

RAG component for unstructured data retrieval (e.g., documents, meeting notes).

Front-end interface for self-service data access.

Solution architecture and configuration documentation.

User guide and knowledge transfer session.

Outcomes

Business users can query CRM data using natural language, reducing ad hoc data requests to IT or BI teams and increasing overall productivity.

Quick access to data supports better targeting and real-time decision-making. Employees and customer service agents can instantly receive critical information on:

Sales performance

Customer segmentation, for personalized marketing and targeting, improving engagement

Lead and opportunity funnel trends to identify bottlenecks, prioritize high-converting leads and optimize the sales process

Sentiment and communication analysis to improve customer satisfaction

Combines structured CRM data and unstructured sources for richer, more actionable insights.

Encourages greater adoption and value from existing CRM systems across the organization.

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