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General AI agent that executes multi-step tasks end to end — research, slides, design, browsing — instead of only answering questions.
Privacy-focused CAPTCHA and bot/fraud-detection service, a drop-in reCAPTCHA alternative for websites and apps.
Weights & Biases is a widely used MLOps platform for experiment tracking, model management and evaluating AI applications.
Open-source browser automation agent that logs into portals and completes web workflows like a human, handling CAPTCHAs and 2FA.
No public pricing
Free trial available
No public pricing
No public pricing
- ✦Autonomous multi-step task execution
- ✦Website and app building
- ✦AI slides, design and image generation
- ✦Manus browser operator
- ✦Wide Research mode
- ✦Cross-platform web, desktop and mobile apps
- ✦AI bot detection
- ✦Transaction fraud protection
- ✦Account-takeover (ATO) defense
- ✦Pull-based SMS MFA
- ✦Private Learning ML risk models
- ✦Two-line reCAPTCHA migration
- ✦Hundreds of integrations
- ✦Experiment tracking and visualization for ML training runs
- ✦Model and artifact versioning and management
- ✦Hyperparameter optimization tooling
- ✦Collaborative dashboards and reports for ML teams
- ✦LLM application tracing and evaluation tooling
- ✦Native CAPTCHA solving without third-party services
- ✦Built-in 2FA/TOTP authentication handling
- ✦Proxy network and geo-targeted browsing
- ✦Explainable AI action logs for auditing runs
- ✦Structured data extraction to CSV/JSON
- ✦Multiple workflow-building methods: chat, SOP upload, recording, visual builder, SDKs
- ✦Python and TypeScript SDKs, on-premise Docker option
- ✦Integrations with Zapier, Make, Salesforce, Slack and more
- →Automate end-to-end digital tasks
- →Produce websites and presentations
- →Conduct broad research
- →Hand off browser tasks to an agent
- →Blocking bots and spam signups
- →Preventing account takeover
- →Reducing transaction and payment fraud
- →Stopping credential stuffing
- →ML engineers tracking and comparing training experiments
- →Research teams versioning datasets and model checkpoints
- →Teams building and evaluating LLM-powered applications
- →Organizations collaborating on machine learning projects
- →Automating accounts-payable invoice downloads across vendor portals
- →Scraping structured web data without an API
- →Filling out applications and compliance forms at scale
- →Lead generation and outreach form submission
- →Resilient browser-based QA/regression testing