Databricks

Building AI Agents That Actually Deliver Business Value

EST

As organizations rapidly adopt generative AI and Agentic solutions, many are discovering that building prototype AI agents is easy—but scaling them into reliable, production-grade systems is not. Challenges around evaluation, governance, deployment, and observability often prevent promising prototypes from delivering real business value.

In this webinar, Aimpoint Digital introduces AgentOps—a practical framework designed to operationalize AI agents at scale. Built on the Databricks Data Intelligence Platform, AgentOps extends MLOps and DevOps principles to address the unique challenges of agentic systems, including non-deterministic behavior, continuous evaluation, and lifecycle management.

We’ll walk through the AgentOps lifecycle, from design and instruction to deployment and monitoring, and demonstrate how organizations can standardize and accelerate agent development using reusable components like Bring Your Own Agent (BYOA), automated evaluation pipelines, and MLflow-based observability.

Through real-world case studies, you’ll see how this approach has reduced evaluation time by over 90%, improved consistency across models, and enabled scalable, multi-region AI deployments.

Whether you’re experimenting with AI agents or looking to bring them into production, this webinar will provide a clear roadmap for building, deploying, and managing agentic systems with confidence.

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Meet the speakers

Andres Uriza

Andrés is a data engineer with a strong background in data science, optimization, operations research, and machine learning. He specializes in making data usable for analysis, modeling, and generating valuable business insights. His expertise includes developing ETL processes, automating architecture solutions using Infrastructure as Code (IaC) and CI/CD, and designing and deploying machine learning systems.

He brings a research-driven mindset to his work, with experience in computer vision, natural language processing, and graph-based machine learning. Andrés is a fast learner, motivated by challenging architectural and scalability problems, and effective both as an independent contributor and as a leader of multidisciplinary teams.

Outside of work, Andrés enjoys spending time with his family, singing, playing guitar, traveling, and exploring cuisines from around the world.

Mafe Roa

Mafe has a strong foundation in data engineering, data science, and machine learning, with expertise in building and deploying end-to-end data pipelines that enhance infrastructure and improve business processes. Her work spans various industries, and she is particularly skilled in leveraging advanced technologies like deep learning, computer vision, and cloud-based systems to deliver impactful results.

Before joining Aimpoint Digital, Mafe worked as a Data Engineer at Factored, where she played a key role in developing ETL infrastructure using Infrastructure as Code (IaC) and streamlining data processes in cloud-based environments. Her earlier experience as a Research Professional focused on applying machine learning models—including classification and regression—to biomedical applications, particularly in lung and breast cancer diagnosis using multimodal data.

She holds both a B.S. and M.S. in Biomedical Engineering from Universidad de los Andes in Bogotá, Colombia. Mafe is AWS Certified as a Cloud Practitioner and holds certifications in Apache Airflow, reflecting her commitment to continuous learning and technical excellence.

Building AI Agents That Actually Deliver Business Value

Meet the speakers

Andres Uriza

Mafe Roa

Let’s talk data. We’ll bring the solutions.

Let’s talk data.
We’ll bring the solutions.