Web Development6 steps
Build a No-Code Website
Create a fully responsive website without writing code using the Siter visual editor and Figma integration.
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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
Create a fully responsive website without writing code using the Siter visual editor and Figma integration.
Leverage TabbyML's open-source, self-hosted AI coding assistant for real-time code completion, intelligent code review, and autonomous task automation using the Agent (Pochi) feature. Maintain full control over your codebase with on-premises deployment and custom model training.
Deploy autonomous AI agents to handle customer support requests end-to-end, from initial contact to resolution, with real-time sentiment analysis and seamless escalation.
A to package, version, and deploy machine learning models using MLEM, enabling seamless CI/CD and multi-environment management.
Evaluate, test, and monitor LLM applications in production using Deepchecks platform for auto-scoring, version comparison, and anomaly detection.
A comprehensive for building, evaluating, and monitoring LLM applications using Parea AI.
Streamlined to automatically refactor existing code, debug errors, and finalize the refactored code for deployment.
Streamlined to automate the code review process: prepare code via automated refactoring, run automated code reviews, document changes, and fix any issues discovered during review.
Set up automated workflows to define inputs and settings, then use AI orchestration tools to coordinate multiple AI agents for task execution.
A practical for developing AI models from initial training to production deployment, with evaluation checkpoints and use of specialized tools.
A focused that generates AI-powered code completions, debugs the result, and finalizes the code for delivery, ensuring high-quality output.
A streamlined to fine-tune, integrate, and orchestrate LLMs for producing accurate, domain-specific outputs efficiently.
A focused to process and interpret natural language inputs, delivering intent and entity extraction.
A streamlined to train a baseline machine learning model, build it into a final AI model, evaluate its performance, and deploy it for real-world use.
A streamlined to train a machine learning model and evaluate its performance using dedicated evaluation tools.
A focused to identify bugs in your codebase using code structure analysis and automated bug detection, ensuring thorough coverage before fixing.
This sets up an AI-powered ticket resolution system using Forethought to automatically analyze and resolve common support tickets, then deploys a Chatbase chatbot to handle customer interactions and finalize resolutions.
Orchestrate multiple AI agents to work together, from initial multi-agent setup through core orchestration to deployment, ensuring seamless collaboration and task completion.
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