From Framework to Impact: Building Agents on Databricks

An industry-leading SAP modernization company aimed to transform its platform into an agentic, AI-driven system. The goal was to embed extensible AI agents directly into the application, integrate chat functionality, and elevate the guided user experiences that customers rely on when working through complex SAP transformations.

This required a reusable AgentOps framework that could be applied across future use cases. The framework had to standardize how agents were built, evaluated, and deployed, with measurable and traceable GenAI models to reduce manual effort while maintaining trust in outputs.  

The company also faced a capability gap. Its engineering team brought deep expertise in SAP and platform development but had limited hands-on experience with LLMOps, agent evaluation patterns, and the architectural decisions required to take GenAI from prototype to production. The company needed a partner who could deliver a production-ready framework while upskilling its engineers in parallel, enabling the team to operate independently within three months. All this had to happen without disrupting ongoing development or compromising performance.

Aimpoint designed and delivered a production-grade custom agent framework on Databricks to showcase efficient development patterns, preeminent agent evaluation methods, and streamlined deployment designs. This “bring-your-own-agent” architecture enabled faster speed to value for ensuing agents while maintaining best practices. Building on this foundation and in close collaboration with client-side technical SMEs, Aimpoint developed a multi-turn chatbot integrated into the client’s existing platform.

Engineer enablement was embedded as a core deliverable throughout the engagement, with a strong focus on upskilling the client team in LLMOps best practices, agent design, evaluation, and production deployment. By month three, client engineers were equipped to independently build, evaluate, and deploy new agents, ensuring long-term sustainability and continued innovation beyond the initial implementation.

This is exactly what I was looking for, and we are already working on next steps to roll out more agentic features. -VP of Engineering