Introduction
Discover how a global enterprise commerce leader used Drizzle:AI’s AgentOps Framework to deploy a production-ready AI platform on AWS in just 4 hours, achieving a 70% cost reduction compared to AWS SageMaker.
Customer Profile
A global leader in the software industry, providing an innovative cloud commerce solution for major enterprise B2B, B2C, and Marketplace clients worldwide.
The Challenge: Bridging the “AI Platform Chasm”
As an innovative software vendor, our client recognized the immense potential of generative AI to enhance their product and boost internal productivity. They had a clear vision for deploying a suite of AI agents to support various business functions, from customer success to sales and engineering.
However, they found themselves stuck in the “AI Platform Chasm.” Their world-class engineering teams were experts in commerce, not in the complex, niche domain of building and managing production-grade AI infrastructure. They faced a critical dilemma:
Build In-House: A slow, expensive, and risky path that would take 12+ months and divert their best talent from their core product.
Use a Managed Service (like AWS SageMaker): A faster but costly option that would lead to vendor lock-in, loss of control over their data, and limited developer freedom.
They needed a solution that could provide the speed of a managed service but with the power, security, and cost-effectiveness of a fully-owned, open-source platform.
The Solution: A Strategic Partnership with Drizzle:AI
The client chose Drizzle:AI to de-risk their AI investment and accelerate their roadmap. We deployed our full suite of solutions on their AWS cloud environment:
The AgentOps Framework: This served as the core foundation. We used our automated pipelines to deploy a secure, scalable, and production-ready AI infrastructure on their AWS account.
Synapse AI: To deliver immediate value, we deployed our AI Knowledge Assistant. It was connected to the client’s internal data sources, providing an instant productivity boost for their teams.
The Enterprise AI Hub: To support their vision of a multi-agent ecosystem, we deployed our secure LLM Gateway. This provided a single, unified API for their custom AI agents to access multiple open-source models with centralized governance and cost control.
The Process: From Planning to Production in Under 4 Days
Our engagement followed a proven, three-phase process that delivered results with unprecedented speed and efficiency.
Phase 1: Planning (3 Days): We conducted intensive workshops with the client’s key stakeholders to understand their needs, define the target architecture, and create a clear, strategic roadmap.
Phase 2: Deployment (4 Hours): Leveraging the power of our automated AgentOps Framework, we deployed the entire end-to-end AI infrastructure on their AWS cloud in just four hours.
Phase 3: Operations (Ongoing): The deployment includes our standard one-year support and maintenance contract. We now act as an extension of their platform team, ensuring the infrastructure remains secure, optimized, and up-to-date.
The Results: A Resounding Success
The Drizzle:AI solution has been a transformative success for the client, delivering tangible results across the board with 100% satisfaction.
Rapid, Enterprise-Wide Adoption: The platform is now actively used by 5 company departments, including technology, product, customer success, sales, and solution architects.
Scalable AI Ecosystem: The Enterprise AI Hub is already serving approximately 10 different client-built AI agents through its secure, unified API.
Massive ROI & Cost Control: The entire platform runs at a total cloud cost of only ~$1,500 per month. This represents a 70% cost saving compared to their initial projections for using serverless cloud based solutions, with the crucial added benefits of full ownership and complete developer freedom.
This partnership has successfully bridged the AI Platform Chasm, turning the client’s AI vision into a production reality at a fraction of the expected time and cost.