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Weights & Biases is a widely used MLOps platform for experiment tracking, model management and evaluating AI applications.
AI super-assistant plus enterprise ML platform: ChatLLM for teams and end-to-end model building for enterprises; broad, pricing not shown.
Generative-AI security platform for watermarking and detecting voice, image, and video deepfakes, built on its own voice-cloning models.
Enterprise AI governance platform to inventory AI systems, assess risk and map controls to regulations like the EU AI Act and NIST.
Privacy-focused CAPTCHA and bot/fraud-detection service, a drop-in reCAPTCHA alternative for websites and apps.
No public pricing
No public pricing
Free trial available
No public pricing
Free trial available
- ✦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
- ✦ChatLLM access to multiple top AI models
- ✦AI agents and automation
- ✦No-code full-stack app creation
- ✦Enterprise generative AI platform
- ✦Structured ML model building
- ✦Optimization and forecasting
- ✦Multimodal deepfake detection for audio, image, and video
- ✦Invisible, persistent watermarking for media provenance
- ✦Real-time deepfake monitoring bot for live meetings
- ✦Voice cloning and text-to-speech generation
- ✦Pay-as-you-go credit-based Flex pricing plan
- ✦Enterprise on-premise deployment and SSO options
- ✦AI/agent registry with shadow-AI discovery
- ✦Continuous, contextual risk intelligence
- ✦Agentic risk and control library
- ✦Policy-to-code with pre-built regulatory policy packs
- ✦Compliance mapping and audit evidence
- ✦GAIA governance assistant and 300+ integrations
- ✦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
- →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
- →Chat with many AI models in one place
- →Build and deploy ML models
- →Automate tasks with AI agents
- →Enterprises verifying caller identity to prevent voice fraud
- →Media companies watermarking content for provenance tracking
- →Security teams monitoring live calls for deepfake impersonation
- →Developers building AI voice agents with cloned voices
- →Comply with the EU AI Act, ISO 42001 and NIST AI RMF
- →Track and govern AI adoption and shadow AI
- →Assess third-party/vendor AI risk
- →Govern AI agents from intake to runtime
- →Blocking bots and spam signups
- →Preventing account takeover
- →Reducing transaction and payment fraud
- →Stopping credential stuffing