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
Data & Analytics
Automate medical coding and enhance clinical documentation using MedPilot's AI-powered platform, which extracts ICD-10, CPT, and HCPCS codes, provides compliance checks, and offers analytics for revenue cycle management.
Monitor dark web sources for leaked credentials, ransomware negotiations, and threat actor activities; analyze and enrich data; and automatically trigger alerts for rapid response.
End-to-end for rapid and accurate infectious disease diagnostics using Biotia's AI-powered metagenomics platform, from sample submission to clinical report generation.
Leverage Korbit to conduct automated code reviews, detect bugs and security vulnerabilities, generate PR descriptions, and provide insights for incident investigation, accelerating the review cycle and improving code quality.
Create, deploy, and optimize enterprise-grade AI agents for customer service across channels with high reliability, compliance, and scalability.
Automate machine learning lifecycle from experiment tracking to model deployment using Polyaxon on Kubernetes.
Use Unify to onboard an AI teammate via live call, execute complex multi-step processes across 3000+ apps, and generate real-time reports with persistent memory.
A streamlined to prepare data, train a neural network model, and evaluate its performance using AI tools.
End-to-end to orchestrate data pipelines: start by performing predictive analytics to inform the pipeline, then orchestrate the data flow, and finally monitor model performance for ongoing reliability.
A focused two-step to analyze code quality: first understand the code structure using Claude Code, then perform a detailed quality analysis with Bito AI.
A streamlined to query, analyze, and report on time-series data, producing decision-ready insights for business stakeholders.
A streamlined for evaluating AI model performance, from deployment to ongoing monitoring. It focuses on setting up the model, running quantitative evaluation, and tracking long-term performance to ensure reliability.
Build and deploy a knowledge graph by retrieving relevant data through vector search, constructing the graph, refining it with multimodal data management, and storing it in a vector database for efficient access.
A streamlined for monitoring system or application performance, from data quality checks through final delivery of a validated performance report and dashboard.
End-to-end for performing vector similarity search, from input preparation to final delivery via a vector database.
A step-by-step for generating educational reports from database analysis, enhancing with narrative text, and packaging into interactive learning content.
Streamlined to generate automated reports from data sources, then refine them into pixel-perfect format for distribution. Uses automation tools and analytical formatting.
Streamlined to create a data pipeline using a drag-and-drop builder and then execute the interface to generate the final output, ensuring a no-code approach for data processing tasks.
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