Corrath
Corrath is an AI gateway that acts as a transparent, high-performance proxy between applications and large language model (LLM) providers. It provides deterministic security filtering, spending controls, and automated failover to protect LLM-powered applications from adversarial threats, budget overruns, and provider outages. The platform integrates via a unified API endpoint, enabling developers to route requests to multiple model backends (including OpenAI, Anthropic, Google, Mistral, and DeepSeek) without changing application code. Key features include real-time prompt injection neutralization, granular per-key spending limits, and a sub-5ms latency circuit breaker that dynamically reroutes traffic during provider downtimes. Corrath also offers cost forecasting, HMAC-SHA256 webhook alerts for threat and cost anomalies, and a dashboard for monitoring request distributions, token spend, and threat categories. Designed for enterprise production environments, Corrath claims 99.99% uptime SLA and processes over 500,000 protected requests and 10 million tokens. It supports multiple project spaces, vaulted API keys, and role-based access controls (RBAC) in higher tiers. An enterprise plan offers on-premise deployment and dedicated support.
- Category
- AI API
- Pricing
- Unknown
Problem solved
Direct integration with LLM APIs exposes applications to prompt injection attacks, budget-busting runaway completions, provider outages that crash services, and compliance risks from leaked PII or credentials. Corrath eliminates these risks by sitting as a secure, low-latency proxy that inspects every request and enforces security, cost, and availability policies.
Use cases
- Protecting chatbots and customer-facing AI assistants from prompt injection and jailbreaks
- Enforcing spending limits across development teams to prevent accidental cloud cost spikes
- Maintaining application uptime by automatically switching LLM providers during outages
- Auditing all LLM requests for PII, security threats, and compliance violations
- Monitoring real-time token usage and latency across multiple AI services
- Integrating a secure gateway for internal agentic workflows that call multiple models
Audience
- Developers
- ML Engineers
- Data Scientists
- Enterprise
Pros
- Sub-5ms latency overhead ensures minimal impact on application performance
- Turnkey protection against prompt injection and adversarial attacks
- Built-in spending controls and cost forecasting prevent budget overruns
- Automatic failover across multiple LLM providers for high availability
- Comprehensive monitoring and webhook alerts for security and cost anomalies
Cons
- Free tier limited to 500 requests per month, unsuitable for production
- Pricing details for paid plans are not publicly listed
- Limited to a fixed set of supported model providers
- Adds an external dependency in the request path, introducing a potential single point of failure
- No open-source version or self-hosted option outside of Enterprise plan
Official website: https://www.corrath.io/
Canonical LambdaBase page: https://www.lambdabase.com/tools/corrath