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Security platform that guards GenAI apps and AI agents against prompt injection, data leaks and misuse for enterprise teams.
Enterprise biometric platform for liveness, deepfake detection and face matching in KYC and fraud-prevention flows.
Cloud platform from the makers of PyTorch Lightning for building, training and deploying AI in browser-based GPU Studios.
Pay-per-use API hub aggregating 1000+ image, video, and audio generation models for developers building AI media pipelines.
Unified API gateway that routes requests to 400+ LLMs across 70+ providers with failover and no subscription.
No public pricing
Free trial available
Free trial available
No public pricing
Free trial available
- ✦Runtime protection for AI agents and apps
- ✦Prompt-injection and jailbreak prevention
- ✦Data-leakage detection in prompts
- ✦Shadow-AI discovery across apps and browsers
- ✦Policy controls by user, app and action
- ✦AI red-teaming and adversarial testing
- ✦Active and passive liveness detection
- ✦Deepfake and AI-generated media detection
- ✦1:1 and 1:N face matching and search
- ✦Age estimation and document verification
- ✦iBeta Level 2 certified, low FAR/FRR
- ✦Lightweight mobile SDKs and REST APIs
- ✦Browser-based Lightning Studios with on-demand GPUs
- ✦PyTorch Lightning training framework
- ✦Model training, fine-tuning and deployment
- ✦Collaborative, shareable ML environments
- ✦Scalable multi-GPU/multi-node compute
- ✦Unified API access to 1000+ image/video/audio generation models
- ✦Pay-per-use pricing billed per image or per second of video
- ✦Includes chat/LLM model access (Claude, GPT, Gemini, etc.) priced per token
- ✦Account tiers unlock higher GPU limits and concurrency
- ✦CLI and desktop app for building workflows
- ✦Enterprise options with dedicated support and custom deployment
- ✦One unified, OpenAI-compatible API for 400+ models
- ✦Automatic provider failover for higher uptime
- ✦Edge routing for low latency
- ✦Custom data and provider policies
- ✦Pay-as-you-go credits usable across any model
- →Securing conversational and RAG agents
- →Governing employee use of AI tools
- →Adversarial testing before deploying GenAI
- →Meeting AI compliance requirements
- →Anti-spoofing liveness checks during KYC onboarding
- →Detecting deepfakes in live video calls
- →Step-up biometric authentication for risky actions
- →Prototype and train ML models in the cloud
- →Fine-tune and deploy foundation models
- →Run reproducible AI experiments collaboratively
- →Integrating AI image/video generation into an app via API
- →Building automated content pipelines needing multiple AI models
- →Testing and comparing many generative models from one account
- →Scaling AI media production with volume-based account tiers
- →Accessing both media-generation and LLM APIs from one platform
- →Accessing many LLMs through one integration
- →Adding provider redundancy to AI apps
- →Comparing model price and performance
- →Powering agents and AI-native products