How to design a reliable fallback system for LLM apps using an AI gateway
Learn how to design a reliable fallback system for LLM applications using an AI gateway.
Drishti Shah
How to secure your entire LLM lifecycle
Learn how Portkey and Lasso Security combine to secure the entire LLM lifecycle from API access and prompt guardrails to real-time detection of injections, data leaks, and unsafe model behavior.
ai security
Why LLM security is non-negotiable
Learn how Portkey helps you secure LLM prompts and responses out of the box with built-in AI guardrails and seamless integration with Prompt Security
LLMOps
Role-based access control (RBAC) for LLM applications
Learn how Role-Based Access Control (RBAC) helps enterprises build AI applications, control access, ensure compliance, and scale securely.
MCP
Building AI agent workflows with the help of an MCP gateway
Discover how an MCP gateway simplifies agentic AI workflows by unifying frameworks, models, and tools, with built-in security, observability, and enterprise-ready infrastructure.
MCP
Using an MCP (Model Context Protocol) gateway to unify context across multi-step LLM workflows
Learn how an MCP gateway can solve security, observability, and integration challenges in multi-step LLM workflows, and why it’s essential for scaling MCP in production.
LLM
How to implement budget limits and alerts in LLM applications
Learn how to implement budget limits and alerts in LLM applications to control costs, enforce usage boundaries, and build a scalable LLMOps strategy.
Azure
Build resilient Azure AI applications with an AI Gateway
Learn how to make your Azure AI applications production-ready by adding resilience with an AI Gateway. Handle fallbacks, retries, routing, and caching using Portkey.
observability
Using metadata for better LLM observability and debugging
Learn how metadata can improve LLM observability, speed up debugging, and help you track, filter, and analyze every AI request with precision.
LLM
What is AI interoperability, and why does it matter in the age of LLMs
Learn what AI interoperability means, why it's critical in the age of LLMs, and how to build a flexible, multi-model AI stack that avoids lock-in and scales with change.
Azure
How to scale GenAI apps built on Azure AI services
Discover how to scale genAI applications built on Microsoft Azure. Learn practical strategies for managing costs, handling prompt engineering, and scaling your AI solutions in enterprise environments.
MCP
MCP vs A2A
Explore the differences between MCP (and A2A, how they address distinct challenges in AI systems, and why combining them could power the next generation of intelligent, interoperable agents.