Cykel

Converts natural language commands into browser automation sequences by parsing user intent and translating it into Playwright or Puppeteer-compatible actions. The system interprets high-level instructions like 'fill the login form and submit' into discrete DOM interactions (click, type, wait), handling dynamic content and JavaScript-rendered pages through headless browser control with intelligent element detection and waits.

Accepts natural language descriptions of API operations and automatically constructs HTTP requests with proper headers, authentication, and payload formatting. The system infers REST endpoints, HTTP methods, and request/response schemas from user intent, handling authentication token management, pagination, and error retry logic without requiring users to write curl commands or API client code.

Chains multiple UI interactions and API calls into sequential workflows with branching logic based on response data or page state. The system maintains execution context across steps, allowing later steps to reference data from earlier steps, and supports conditional branching (if-then-else) based on extracted values, HTTP status codes, or DOM element presence without requiring explicit programming.

Identifies and interacts with UI elements on JavaScript-rendered pages using computer vision and DOM analysis rather than brittle selectors. The system combines visual element recognition with semantic understanding of page structure, allowing it to locate buttons, forms, and links even when their CSS selectors change, and handles dynamic content loading, modal dialogs, and asynchronous rendering without explicit waits.

Extracts structured data from web pages and API responses using natural language field descriptions, automatically parsing tables, lists, and nested data structures. The system infers data types and formats from context, handles pagination automatically, and can transform extracted data into specified output formats (CSV, JSON, database records) without requiring regex patterns or custom parsing code.

Handles login flows, session persistence, and credential management across different authentication schemes (username/password, OAuth, SAML, API keys) without exposing credentials in logs or workflows. The system maintains authenticated sessions across multiple steps, automatically refreshes tokens, and manages cookie-based sessions for stateful interactions across websites and APIs.

Detects failures in automation steps (network errors, timeouts, validation failures) and applies configurable retry strategies with exponential backoff, circuit breaker patterns, and fallback actions. The system distinguishes between transient errors (retry) and permanent failures (escalate), logs detailed error context for debugging, and can trigger alternative workflows or notifications on critical failures.

Schedules automation workflows to run on recurring intervals (hourly, daily, weekly) or triggered by external events (webhook, API call, file upload), and provides real-time execution monitoring with step-by-step logs, performance metrics, and execution history. The system tracks workflow duration, success rates, and resource usage, enabling teams to identify bottlenecks and optimize automation performance.

Provides a drag-and-drop visual interface for constructing automation workflows, with automatic conversion between visual workflows and natural language descriptions. Users can build workflows visually, then refine them with natural language instructions, or start with natural language and visualize the resulting workflow structure for validation and debugging.