How to build a production-ready financial report analysis pipeline using multiple specialized AI agents with ZenML for orchestration, SmolAgents for lightweight agent implementation, and LangFuse for observability and debugging.
FloraCast is a production-ready template that shows how to build a forecasting platform—config-driven experiments, model versioning/staging, batch inference, and scheduled retrains—with ZenML and Darts.
Learn how to build production-ready agentic AI workflows that combine powerful research capabilities with enterprise-grade observability, reproducibility, and cost control using ZenML's structured approach to controlled autonomy.
Discover why production teams are treating agentic workflows as MLOps evolution, not revolution—plus how ZenML achieved 200x performance improvements for enterprise ML operations. Real insights from 130+ MLOps engineers on building reliable AI systems.
Discover how to optimize GPU utilization in Kubernetes environments by integrating NVIDIA's KAI Scheduler with ZenML pipelines, enabling fractional GPU allocation for improved resource efficiency and cost savings in machine learning workflows.
OncoClear is an end-to-end MLOps solution that transforms raw diagnostic measurements into reliable cancer classification predictions. Built with ZenML's robust framework, it delivers enterprise-grade machine learning pipelines that can be deployed in both development and production environments.
Can automated classification effectively distinguish real-world, production-grade LLM implementations from theoretical discussions? Follow my journey building a reliable LLMOps classification pipeline—moving from manual reviews, through prompt-engineered approaches, to fine-tuning ModernBERT. Discover practical insights, unexpected findings, and why a smaller fine-tuned model proved superior for fast, accurate, and scalable classification.
Learn how to build, fine-tune, and deploy multimodal LLMs using ZenML. Explore LLMOps best practices for deployment, real-time inference and model management.
Seamlessly automating the journey from training to production, ZenML's new NLP project template offers a comprehensive MLOps solution for teams deploying Huggingface models to AWS Sagemaker endpoints. With its focus on reproducibility, scalability, and best practices, the template simplifies the integration of NLP models into workflows, complete with lineage tracking and various deployment options.
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