Leading European Pharma Empowers 200+ Sales Representatives with Agentic AI Assistant

Overview

A Renowned European pharmaceutical company specializing in dermatology and skincare, with presence in over 80 countries, partnered with Neurons Lab to transform their sales operations through AI-powered automation. The company operates through a sophisticated commercial network of 200+ sales representatives serving pharmacies across multiple territories.

The sales organization operates through a hierarchical structure with four distinct levels, each requiring different data access permissions and analytics capabilities. The company maintains extensive data infrastructure including BigQuery data warehouses, product catalogs with 1,500+ SKUs, and real-time pharmacy sales analytics.

This project delivered an AI-powered sales assistant using Amazon Bedrock foundation models and MCP (Model Context Protocol) architecture to provide instant, territory-aware access to business intelligence.

Challenges

Sales representatives were spending more than four hours per week manually retrieving and validating territory-specific performance data. Accessing meaningful analytics required SQL knowledge or support from technical teams, limiting adoption of self-service reporting.

During live pharmacy meetings, retrieving product availability or pricing information could take between 15 and 60 minutes. This delay reduced responsiveness and weakened commercial conversations.

An existing chatbot solution failed to resolve these issues. It suffered from latency exceeding 15 seconds, inconsistent knowledge integration, and no conversational memory. Each interaction required repeated context-setting, making it unsuitable for field use.

• Manual Data Analysis Burden: 200+ sales representatives spent 4+ hours weekly searching for territory-specific data, diverting time from customer-facing activities.
• Technical Barriers to Analytics: Self-service analytics adoption was limited due to technical barriers requiring SQL knowledge, creating dependency on technical teams.
• Lack of Conversational Continuity: Sales representatives had to repeatedly provide context in each interaction due to lack of conversation history.
• Delayed Customer Responses: Field sales experienced delays of 15–60 minutes when searching for product information and pricing data during customer interactions.
• Complex Hierarchical Access Requirements: The organization required territory-based data access controls across four hierarchy levels while maintaining data security.
• Poor Existing AI Performance: The existing chatbot suffered from 15+ second latency, poor knowledge integration, and slow feature development.

Solution

Neurons Lab developed an agentic AI sales assistant powered by Amazon Bedrock foundation models using MCP (Model Context Protocol) architecture. The solution leverages Amazon Bedrock AgentCore capabilities for secure, scalable agent deployment with built-in memory and observability services.

MCP Architecture

The solution implements a modular MCP architecture enabling seamless integration of multiple data sources:

• SQL MCP Server: Territory-filtered analytics queries with row-level security and optimized query performance achieving sub-5-second response times.
• Spreadsheet MCP Server: Dynamic Google Sheets API integration for real-time product/pricing data across 1,500+ SKUs with automated validation.
• Memory MCP Server: PostgreSQL database with pgvector extension for semantic similarity search, enabling ChatGPT-like conversational continuity with 85% recall accuracy.

Tiered Model Strategy

The solution implements intelligent model routing for cost optimization:

• Amazon Nova Lite: Primary model for complex queries (94% accuracy, 280ms latency, $0.06/1K tokens)
• Amazon Nova Micro: Cost-optimized model for simple lookups (87% accuracy, 150ms latency)

Claude 4.5 Sonnet: Reserved for sophisticated analytics requiring highest accuracy

Security and Access Control

The solution implements comprehensive security controls including territory-based row-level security with 100% enforcement across all hierarchy levels, token-based authentication, and full audit logging through AWS CloudTrail. All data is encrypted at rest using AWS KMS and in transit using TLS 1.3.

Results

• Response Time Transformation: Reduced end-to-end response time from 15+ seconds (previous system) to 4.2 seconds, matching industry-leading AI assistants.
• Data Access Democratization: 200+ sales representatives gained instant access to territory-specific pharmacy performance metrics without SQL knowledge.
• Conversational Intelligence: Chatbot-like conversational continuity with 85% recall accuracy across sessions, eliminating repetitive context-setting.
• Cost-Effective AI: Achieved 75% cost savings compared to GPT-4 baseline while maintaining 94% accuracy on business-critical queries.
• Projected ROI: Business case analysis projects 101–303% ROI with $567K–$1.134M annual benefits from sales productivity improvements.

Conclusion

This case study demonstrates how companies can leverage agentic AI solutions to vastly improve efficiency of sales operations. By implementing a modular MCP architecture with tiered Amazon Nova models, the platform delivers enterprise-grade accuracy and performance while achieving significant cost savings.

The solution successfully addresses the complex requirements of hierarchical sales organizations, providing territory-aware data access with comprehensive security controls. The conversational memory system enables natural interactions that improve over time, while the serverless architecture ensures scalability for growing query volumes.

The AI-powered sales assistant serves as a foundation for future enhancements including voice-to-voice interaction, CRM integration, and multi-country deployment, positioning the organization for continued innovation in AI-powered commercial operations.

About Neurons Lab

Bridge the gap between AI potential and industry reality.

We help organizations in highly regulated industries, including pharmaceuticals, translate strategic AI intent into production-ready agentic systems — delivered with speed, grounded in domain expertise, and designed for scale.

Small, senior teams and pre-built agent components accelerate delivery to production in weeks, without compromising compliance, governance, or operational fit. Through embedded delivery, ownership is transferred to internal teams and capability expands beyond the initial use case.

Our proven success across 100+ engagements — including work with global enterprises operating under strict regulatory and operational constraints — combined with AWS Advanced GenAI Partner status, provides the expertise required to deploy secure, scalable systems that deliver measurable commercial impact.