With our Agentic AI services, you'll enjoy a range of benefits, including cost-effective and scalable capacity for running multi-step AI workloads, support for industry-standard agent frameworks, and seamless integration with your existing data and operational systems. Our services handle many of the underlying infrastructure management tasks, allowing your team to focus on developing and innovating your AI-driven applications.
Whether you're a small startup or a large enterprise, our team is equipped to tailor the implementation of Agentic AI solutions to your needs. We leverage Amazon Bedrock AgentCore and the Strands Agents SDK available on AWS, ensuring a robust architecture and seamless integration. We'll work closely with you to understand your requirements and provide ongoing support to ensure your success in the AWS Cloud.
Unlock the full potential of AI agents with our Agentic AI Consulting Services. Contact us today to get started on your journey to efficient, scalable, and secure agentic AI deployment in the AWS Cloud.
A leading cooperative in the Consumer Goods and Dairy industry, with an extensive B2B commercial network serving hundreds of clients — from small retailers to large food service operators — across multiple geographic regions. Their nationwide sales team manages recurring demand across diverse product categories, seasonal cycles, and client profiles, requiring consistent and data-driven commercial execution at scale.
The client required a tool that would allow their sales team to access personalized, data-driven product recommendations for each B2B client visit — replacing a fully manual and experience-dependent process. The need was to enhance commercial efficiency and recommendation quality by automating the analysis of transactional history, seasonal demand, geographic trends, and cross-sell patterns, which were previously handled manually and inconsistently across the team. After a thorough analysis of the data landscape and required integrations, we identified that a standard retrieval-augmented generation (RAG) approach would be insufficient: the recommendations required real-time reasoning across multiple live data sources simultaneously, with calibrated quantities and explainable outputs ready for the sales rep to use directly in the client conversation.
We developed an agentic AI system powered by Amazon Bedrock, using the Strands Agents SDK and Bedrock AgentCore as the managed runtime for the agent's analytical tools. The agent orchestrates a structured reasoning chain over six MCP-based tools backed by Amazon Athena — querying client purchase history, seasonal demand patterns, geographic market statistics, trend signals, and cross-sell opportunities — to generate personalized, explainable recommendations with calibrated quantities for each client. A weekly batch inference pipeline built on AWS Glue, Step Functions, and the Bedrock Batch Inference API precomputes recommendations for the full client portfolio and caches them in Amazon DynamoDB for instant retrieval. A real-time on-demand path, triggered via Amazon API Gateway and processed by an async Lambda dispatcher, handles ad-hoc recommendation requests during sales visits in under 30 seconds.
The use of Amazon Bedrock AgentCore and cross-region inference profiles in our agentic solution offers significant advantages over static or rule-based recommendation approaches. The multi-step reasoning loop over six live data tools enables context-aware, data-fresh recommendations that simultaneously account for current inventory dynamics, geographic demand variations, seasonal trends, and cross-sell momentum — something a pre-indexed knowledge base cannot provide. This capability not only improves recommendation accuracy and catalog coverage but also makes the outputs directly usable by sales representatives: each recommendation includes calibrated quantities and a natural-language rationale, streamlining the preparation and execution of client visits. The dual-model architecture (Claude Sonnet 4.6 for complex agentic reasoning, Claude Haiku 4.5 for cost-optimized batch volume) delivers 98% of AWS run-rate in GenAI services while keeping total monthly cost within budget through Bedrock Batch discounts and a DynamoDB precomputed cache that serves over 90% of real-time requests at sub-millisecond latency.
The implementation of this agentic AI solution has dramatically accelerated sales preparation and recommendation consistency across the team. Sales representatives can now access personalized, data-driven recommendations for every client in under one minute — compared to 30 to 45 minutes of manual preparation previously required.
The solution is built entirely on serverless and fully managed AWS services, eliminating the need to provision or manage any infrastructure. AWS Lambda scales automatically to handle concurrent on-demand recommendation requests without capacity planning, while Amazon API Gateway provides a highly available, regionally redundant entry point that absorbs traffic spikes with no manual intervention. The weekly batch inference pipeline — orchestrated by AWS Step Functions and AWS Glue — processes the full client portfolio in parallel using the Bedrock Batch Inference API, ensuring timely delivery of precomputed recommendations regardless of portfolio size. Results are cached in Amazon DynamoDB, a serverless NoSQL database engineered for single-digit millisecond latency at any scale, serving over 90% of real-time requests with sub-millisecond response times. Amazon Bedrock's cross-region inference profiles add an additional layer of availability by automatically routing inference traffic across AWS regions, preventing throttling and ensuring consistent throughput even during peak usage periods.
Security is enforced across every layer of the stack. IAM least-privilege policies govern all Lambda execution roles, while CloudFront with Origin Access Control and API Gateway with a Lambda authorizer secure the edge. All data at rest is encrypted via AWS KMS with customer-managed keys, and all data in transit is protected by TLS certificates managed through AWS Certificate Manager. Amazon GuardDuty provides continuous threat detection and Amazon Inspector performs automated vulnerability assessments across the workload. AWS CloudTrail and Amazon CloudWatch deliver full audit traceability and operational observability, with alarms configured to surface issues before they impact the sales team.