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applied-zenml

12 posts with this tag

How to Build a Multi-Agent Financial Analysis Pipeline with ZenML and SmolAgentsHow 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.agentshuggingfacezenml-project+1 Haziqa Sajid2025
Production-Ready AI Agents: Why Your MLOps Stack is the Missing PieceLLMOpsllmagents+1Alex Strick van Linschoten2025
ZenML's MCP Server Supports DXT: Making MLOps Conversations FrictionlessZenML's new DXT-packaged MCP server transforms MLOps workflows by enabling natural language conversations with ML pipelines, experiments, and infrastructure, reducing setup time from 15 minutes to 30 seconds and eliminating the need to hunt across multiple dashboards for answers.mcpagentsAlex Strick van Linschoten2025
Steerable Deep Research: Building Production-Ready Agentic Workflows with Controlled AutonomyLearn 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.zenml-projectllmagentsAlex Strick van Linschoten2025
Query Rewriting in RAG Isn’t Enough: How ZenML’s Evaluation Pipelines Unlock Reliable AIAre your query rewriting strategies silently hurting your Retrieval-Augmented Generation (RAG) system? Small but unnoticed query errors can quickly degrade user experience, accuracy, and trust. Learn how ZenML's automated evaluation pipelines can systematically detect, measure, and resolve these hidden issues—ensuring that your RAG implementations consistently provide relevant, trustworthy responses.RAGLLMOpsJayesh Sharma2025
How to Finetune Phi 3.5 with ZenMLMaster cloud-based LLM finetuning: Set up infrastructure, run pipelines, and manage experiments with ZenML's Model Control Plane for Microsoft's latest Phi model.foundationmodelsllmmodel-control-plane+4Alex Strick van Linschoten2024
How to Finetune Llama 3.1 with ZenMLMaster cloud-based LLM finetuning: Set up infrastructure, run pipelines, and manage experiments with ZenML's Model Control Plane for Meta's latest Llama model.foundationmodelsllmmodel-control-plane+4Alex Strick van Linschoten2024
Productionalizing NLP models with ZenMLSeamlessly 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.zenml-projectdeploymenthuggingface+1Safoine El khabich2023
Huggingface Model to Sagemaker Endpoint: Automating MLOps with ZenMLDeploying Huggingface models to AWS Sagemaker endpoints typically only requires a few lines of code. However, there's a growing demand to not just deploy, but to seamlessly automate the entire flow from training to production with comprehensive lineage tracking. ZenML adeptly fills this niche, providing an end-to-end MLOps solution for Huggingface users wishing to deploy to Sagemaker.sagemakerhuggingfacemodel-control-planeHamza Tahir2023
Will they stay or will they go? Building a Customer Loyalty PredictorWe built an end-to-end production-grade pipeline using ZenML for a customer churn model that can predict whether a customer will remain engaged with the company or not.evergreenmachine-learningmlops+2Ayush Singh2022
How to improve your experimentation workflows with MLflow Tracking and ZenMLUse MLflow Tracking to automatically ensure that you're capturing data, metadata and hyperparameters that contribute to how you are training your models. Use the UI interface to compare experiments, and let ZenML handle the boring setup details.evergreenintegrationstooling+1Alex Strick van Linschoten2022
Predicting the winner of a DotA 2 match using distributed deep learning pipelinesZenML makes it easy to setup training pipelines that give you all the benefits of cached steps.machine-learningpipelineszenmlBaris Can Durak2020

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zenml mlops evergreen agents LLMOps tooling llm bigger-picture open-source kitaru infrastructure genai All 116 tags →

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applied-zenml

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