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Unified API gateway that routes requests to 400+ LLMs across 70+ providers with failover and no subscription.
AML and fraud compliance platform pairing transaction monitoring, screening, and explainable AI agents for financial institutions.
Cloud DLP and CASB that classifies and protects sensitive data across SaaS apps using deep learning (now Palo Alto Networks).
AI-focused cloud offering NVIDIA GPU compute, storage and MLOps tooling for training and inference at scale, with usage-based pricing.
Fast, low-cost AI inference provider running LLMs on custom LPU chips via GroqCloud's pay-as-you-go API.
No public pricing
No public pricing
- ✦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
- ✦Real-time transaction monitoring and rule engine
- ✦Explainable AI forensics agents
- ✦Dynamic risk scoring
- ✦Watchlist/sanctions/PEP screening
- ✦AI-native case management
- ✦Automated SAR filing to FinCEN and 70+ GoAML countries
- ✦Deep-learning data classification (99.5% claimed accuracy)
- ✦Cloud DLP across SaaS applications
- ✦One-click deployment across apps, devices and users
- ✦End-user self-remediation of violations
- ✦Broad SaaS integrations
- ✦Insider-threat and breach monitoring
- ✦NVIDIA GPU instances (H100, H200, B200, GB200)
- ✦On-demand and preemptible GPU pricing
- ✦High-performance and object storage
- ✦Managed Kubernetes and Slurm (Soperator)
- ✦Serverless and managed inference (Token Factory)
- ✦MLOps tooling and 24/7 expert support
- ✦Commitment discounts up to 35%
- ✦LPU custom inference hardware
- ✦GroqCloud tokens-as-a-service API
- ✦High-speed, low-latency inference
- ✦Pay-as-you-go token pricing
- ✦Free API key to start
- ✦Broad open-model support
- →Accessing many LLMs through one integration
- →Adding provider redundancy to AI apps
- →Comparing model price and performance
- →Powering agents and AI-native products
- →AML compliance and monitoring
- →Reducing false-positive alerts
- →Streamlining fincrime investigations and SAR filing
- →Prevent data leaks across SaaS apps
- →Classify and monitor sensitive data
- →Reduce breaches from human error
- →Give security teams cloud data visibility
- →Train large AI/ML models on GPU clusters
- →Run scalable inference workloads
- →Store and manage large training datasets
- →Run Slurm/Kubernetes AI pipelines
- →Running LLM inference at high speed
- →Cutting inference costs at scale
- →Powering low-latency AI chat apps
- →Serving models via a hosted API