LLM Gateway for Secure, Controlled AI
Route, secure, and monitor every LLM interaction through a unified gateway. Agumbe provides built-in guardrails for prompt injection, PII, and policy enforcement — so your applications stay safe, compliant, and production-ready.
Secure Every Prompt
Protect your applications from prompt injection, data leakage, and unsafe outputs with built-in guardrails.
Control and Govern Usage
Define policies for model access, rate limits, and usage across teams with centralized control.
Observe Every Interaction
Track requests, responses, latency, and failures with full visibility across your LLM stack.
Prompt Injection Protection
Detect and block malicious prompts before they reach your models.
PII & Secret Redaction
Automatically detect and mask sensitive data in requests and responses.
Multi-Provider Routing
Switch between OpenAI, Anthropic, and others without changing application code.
Control Your Entire LLM Layer
Unified Control
Apply guardrails, routing, and policies consistently across all environments.
Accelerate your speed of innovation while easing data privacy, governance and compliance. Build fast with data confidence.
Data Integrity
Reliable and Safe LLM Interactions
End-to-end LLM Observability
Monitor every request and response across your LLM applications. Detect failures, track latency, and gain full visibility into usage patterns.
Understand how your models behave in production and optimize continuously.
Governance and Access Control
Control access to models and APIs with RBAC and secure endpoints.
Ensure compliance with centralized policies and audit trails.
Developer-Friendly APIs
Integrate the gateway into your applications with simple APIs and SDKs.
Route LLM calls through Agumbe without changing your architecture.
Route, control, and optimize LLM traffic across providers and environments with full visibility and policy enforcement.
Request Routing & Failover
Route requests across multiple LLM providers with intelligent fallback and retry strategies.
Ensure high availability and reliability for every LLM interaction.
Rate Limits & Usage Control
Control how LLMs are used across users, teams, and environments with configurable limits and quotas.
Observability, Trace
Instrumented telemetry and observability across the lifecycle of models.
Ability to tag and track the state of a model (e.g., in training, in validation, deployed, retired) to streamline workflows.
Data Versioning
Data versioning, experimentation, model metadata and interactions through a unified interface.
Platform API, CLI
Serverless API for model serving and fine-tuning.
Gain control over experimentation, infrastructure, compute and data via extensible Platform APIs and friendly CLI.
Manage experimentation via native shell commands.
Want to explore more?
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