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
This helps identify unusual patterns in financial data by first preparing and analyzing transaction data, then forecasting expected performance to establish a baseline, and finally detecting anomalies that deviate from the norm.
A step-by-step to assess individual health risks using symptom analysis, real-world evidence, medical literature summarization, and clinical data analysis to produce a reliable risk assessment report.
Streamline demand forecasting by preparing inventory data, running the forecast model, detecting anomalies, and generating business reports.
A streamlined to prepare data, build predictive models, and monitor their ongoing performance for reliable business insights.
A focused to define extraction schema, perform AI-driven web scraping, validate results, and deliver structured data for analysis.
A streamlined to discover biomarkers by extracting relevant data, analyzing genomic and biological data, and generating actionable insights for drug development.
Streamlined to generate production-ready code using AI, starting with dbt-specific preparation and then generating the final source code.
A focused that prepares time-series data, applies anomaly detection algorithms, and produces a comprehensive report of detected anomalies for business stakeholders.
Practical plan to set up ongoing monitoring of ML model performance using SAS Viya for tracking, then predictive analytics to uncover drift or degradation, followed by deploying refined monitoring dashboards, and finally orchestrating automated reporting pipelines.
A streamlined to prepare data, train models, evaluate performance, and deploy the final model for real-world use.
Extract database schema and then generate SQL queries based on the schema, ensuring the queries are tailored to the data structure.
A practical to collect customer feedback via natural language queries, analyze sentiment using AI, and produce actionable business reports for customer experience improvement.
Train, deploy, and monitor machine learning models at scale — from raw dataset to a live API endpoint with full observability.
Practical execution plan for natural language to sql generation with clear steps, mapped tools, and delivery-focused outcomes.
Practical execution plan for convert natural language to sql with clear steps, mapped tools, and delivery-focused outcomes.
Practical execution plan for data curation with clear steps, mapped tools, and delivery-focused outcomes.
Practical execution plan for data masking with clear steps, mapped tools, and delivery-focused outcomes.
Practical execution plan for automate financial reporting with clear steps, mapped tools, and delivery-focused outcomes.
