1,000 workflows · plans that ship
Each workflow is a step-by-step plan. Each step is a real tool. We tested every one of them — if a step's broken, the workflow is gone.
Engineering & Code domain
Accelerate your development cycle from initial prototype to production-ready deployment.
Focus area
Automation & Integrations
Set up a customer service chatbot by first preparing a knowledge base with CustomGPT.ai, then building the chatbot using Eloquence AI, and finally deploying it via Accenture AI Solutions to automate customer interactions.
A streamlined to enforce coding standards by analyzing code structure, applying automated fixes, refactoring, debugging, and finalizing the code for production.
A practical to optimize an existing AI model's inference speed and resource efficiency using monitoring insights and dedicated optimization tools.
A step-by-step plan to fine-tune a large language model: prepare the base model, optimize hyperparameters, execute fine-tuning, and orchestrate the final model for deployment.
A step-by-step plan to set up, configure, and deploy an automated customer service system using AI chatbots and engagement tools, from initial support automation to final delivery.
A streamlined to complete unfinished code, including refactoring, completion, debugging, and structural analysis for a robust final output.
A streamlined to train, evaluate, optimize, and deploy deep learning models using state-of-the-art frameworks and tools for production-ready results.
A concise to identify and fix bugs in code using AI-powered debugging and explanation tools.
A streamlined to generate concise code snippets using an AI assistant and then validate the logic with an explanation step, ensuring high-quality reusable code blocks.
Train a machine learning model using TensorFlow or Kaggle, then deploy it to production with Seldon Core or Baseten for real-time inference via API endpoints.
A focused to produce comprehensive code documentation by first analyzing the codebase structure, then generating documentation using a suitable AI tool, and finally adding detailed explanations for complex logic.
Streamline customer support and engagement through automated chatbots and interaction management, from initial setup to live deployment.
End-to-end for building and deploying a predictive model, from initial training to fine-tuning and final prediction generation, using tools like TensorFlow, Tenstorrent, and Babylon.
A streamlined for designing and optimizing AI prompts through iterative refinement and visual validation.
Build and deploy applications faster by letting an autonomous agent handle the boilerplate and logic.
From logic definition to production-ready code with automated testing and deployment — a repeatable pipeline for shipping software features.
Ship features faster by delegating architecture, implementation, testing, and deployment to specialized AI coding agents.
Practical execution plan for automate mlops workflows with clear steps, mapped tools, and delivery-focused outcomes.
