> For the complete documentation index, see [llms.txt](https://docs.zenml.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.zenml.io/user-guides/readme.md). # Overview Guides, examples and projects Discover how to build production-ready ML pipelines with ZenML and evaluate agentic systems with Kitaru through our curated learning resources. Whether you're looking for step-by-step instructions, complete project implementations, or specific examples, you'll find resources to accelerate your workflow. [Kitaru](https://docs.zenml.io/kitaru) is ZenML's sibling project for evals and improvement loops for agentic systems. It works from recorded or imported production traces through investigation, cohorts, evaluators, replay experiments, regression testing, and CI. ZenML orchestrates pipelines; Kitaru runs this workflow on its own server and workers. ## Guides Step-by-step instructions to help you master ZenML concepts and features.


Starter Guide	Get started with ZenML fundamentals and set up your first pipeline	starter.png	Starter guide
Production Guide	Move your ML pipelines from development to production	prod.png	Production guide
LLMOps Guide	Build and deploy Large Language Model pipelines	llm.png	LLMOps guide
Agent evals → Kitaru	Turn production traces into investigations, evaluators, cohorts, replay experiments, and regression checks in the Kitaru docs.	kitaru.png	https://docs.zenml.io/kitaru
Tutorials	Deep dives into advanced topics	prod.png	Organizing Stacks Pipelines Models

## Projects Complete end-to-end implementations that showcase ZenML in real-world scenarios.\ [See all projects in our website →](https://www.zenml.io/projects)


FloraCast	A production-ready MLOps pipeline for time series forecasting using ZenML and Darts, featuring TFT-based training and scheduled batch inference.	zencoder.jpg	https://www.zenml.io/projects/floracast
LLM-Complete Guide	Production-ready RAG pipelines from basic retrieval to advanced LLMOps with embeddings finetuning and evals.	llm-complete-guide.jpg	https://github.com/zenml-io/zenml-projects/tree/main/llm-complete-guide
Retail Forecast	A robust MLOps pipeline for retail sales forecasting designed for retail data scientists and ML engineers.	nightwatch.jpg	https://www.zenml.io/projects/retail-forecast
Research Radar	Automates research paper discovery and classification for specialized research domains.	researchradar.jpg
OncoClear	A production-ready MLOps pipeline for accurate breast cancer classification using machine learning.	magicphoto.jpg	https://www.zenml.io/projects/oncoclear
Sign Language Detection with YOLOv5	End-to-end computer vision pipeline	yolo.jpg	https://www.zenml.io/projects/sign-language-detection-with-yolov5
ZenML Support Agent	A production-ready agent that can help you with your ZenML questions.	support.jpg	https://www.zenml.io/projects/zenml-support-agent
OmniReader	A scalable multi-model OCR workflow framework for batch document processing and model evaluation.	gamesense.jpg	https://www.zenml.io/projects/omnireader
EuroRate Predictor	Turn European Central Bank data into actionable interest rate forecasts with this comprehensive MLOps solution.	eurorate.jpg	https://www.zenml.io/projects/eurorate-predictor

## Examples Focused code snippets and templates that address specific ML workflow challenges.\ [See all examples in GitHub →](https://github.com/zenml-io/zenml-projects)


Quickstart	Bridging Local Development and Cloud Deployment	example-01.png	https://github.com/zenml-io/zenml/blob/main/examples/quickstart
End-to-End Batch Inference	Supervised ML project built with the ZenML framework and its integration.	example-02.png	https://github.com/zenml-io/zenml/tree/main/examples/e2e/README.md
Agent Architecture Comparison	Compare AI agents with LangGraph workflows, LiteLLM integration, and automatic visualizations.	example-06.png	https://github.com/zenml-io/zenml/blob/main/examples/agent_comparison
Agent Framework Integrations	Production-ready integrations for 11 popular agent frameworks including LangChain, CrewAI, AutoGen, and more.	example-06.png	https://github.com/zenml-io/zenml/tree/main/examples/agent_framework_integrations/README.md
Deploying Agents	Document analysis service with pipelines, evaluation, and embedded web UI.	example-07.png	https://github.com/zenml-io/zenml/blob/main/examples/deploying_agent
Agent Outer Loop	Agent training and evaluation loop: evolve a generic agent into a specialized support system through intent classification and model training.	example-07.png	https://github.com/zenml-io/zenml/blob/main/examples/agent_outer_loop
Basic NLP with BERT	Build NLP models with production-ready ML pipeline framework	example-03.png	https://github.com/zenml-io/zenml/tree/main/examples/e2e_nlp/README.md
Computer Vision with YoloV8	End-to-end computer vision pipeline with modular design	example-04.png	https://github.com/zenml-io/zenml/tree/main/examples/computer_vision/README.md
LLM Finetuning	LLM fine-tuning pipeline with PEFT approach	example-05.png	https://github.com/zenml-io/zenml/tree/main/examples/llm_finetuning/README.md
Replay-Based Agent Evals (Kitaru)	Runnable Kitaru starter: turn real traces from a PydanticAI returns agent into replayable evals, with human review and bounded replay.		https://github.com/zenml-io/kitaru-template

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