BlueAlpha
Atlanta, GA
Ecommerce Technology, Personalization and Recommendation Systems
Amazon Bedrock, Amazon S3, Amazon RDS, Amazon ECS, AWS Fargate
BlueAlpha is a marketing intelligence and personalization platform that helps teams make faster decisions about how to allocate and optimize advertising spend. As customer and campaign data grew, BlueAlpha needed a scalable way to answer complex marketing questions and refresh audience segmentation without heavy manual analysis. Avahi delivered an AWS-based, agentic backend that turns natural language questions into structured queries, executes them against BlueAlpha’s data sources, and returns clear, data-backed responses. The result is a reusable foundation for automated insights and personalization workflows, with an architecture designed to integrate cleanly into BlueAlpha’s existing AWS environment.
BlueAlpha provides marketing analytics and decision intelligence for digital campaigns, helping organizations understand performance drivers, forecast the impact of budget changes, and deliver more relevant customer experiences through data-driven insights and segmentation.
BlueAlpha’s users and internal teams still spent significant time pulling performance data, aggregating it, and turning it into answers stakeholders could act on. In practice, customers were dedicating 20 to 30 percent of their time to manual querying and analysis, and BlueAlpha often needed 4 to 6 hours to compile performance insights for each client.
At the same time, key segmentation and personalization workflows were static and rulebased, requiring ongoing manual effort to update as behavior and campaign conditions changed. BlueAlpha needed to validate whether agentic GenAI could orchestrate data access, automate analysis, and produce consistent, explainable outputs through an API-driven approach.
If left unaddressed, the manual effort would continue to limit scale, slow down optimization cycles, and make it harder to deliver timely recommendations across more customers, channels, and use cases.
BlueAlpha selected AWS to align the solution with its existing cloud footprint and to access foundation models through Amazon Bedrock. This provided a managed, enterprise-ready path for model inference while keeping the workflow close to BlueAlpha’s core datasets and security controls.
AWS also enabled a straightforward integration pattern across data stores and services already in use, including querying model outputs stored in Amazon RDS and Amazon S3, and packaging the agent service for future deployment into BlueAlpha’s Amazon ECS on AWS Fargate environment.
BlueAlpha chose Avahi because of Avahi’s deep experience delivering production-aligned GenAI architectures on AWS, including agent orchestration patterns, tool design, and secure data access. As a Premier Tier AWS Partner, Avahi brought a practical approach that prioritized measurable workflow automation and clean integration points.
To reduce technical risk, Avahi delivered two compatible orchestration implementations, a LangGraph-based agent system and a Strands MCP-based agent system. This gave BlueAlpha flexibility to adopt the approach that best fit its roadmap while reusing the same modular tool and API patterns.
– Solution architecture and design for an agentic analytics and personalization backend
– LangGraph multi-agent implementation for query routing, execution, and response generation
– Strands MCP server and agent implementation with modular tool abstractions
– FastAPI endpoints for orchestration and response delivery
– Tooling for CSV reading, metric extraction, and reporting workflows
– SSE event streaming integration for real-time tool invocation and agent updates
– Documentation for both implementations, including integration guidance and demo workflow
BlueAlpha validated that agentic GenAI can automate core analysis and segmentation workflows that were previously manual and slow to update. By combining deterministic tooling with Amazon Bedrock model reasoning, the engagement established a reusable pattern for answering marketing questions, generating insights, and supporting future personalization features through a single API-driven framework.
With two orchestration options and modular tools, BlueAlpha can extend the solution to additional datasets and use cases while maintaining consistent behavior, explainability, and developer-friendly maintainability.
Founder, Bravo Foxtrot
