Bringing control and visibility to Claude Code with an AI Gateway
Learn how to make Claude Code enterprise-ready with Portkey. Add visibility, access control, logging, and multi-provider routing to scale safely across teams.
Drishti Shah
Retries, fallbacks, and circuit breakers in LLM apps: what to use when
Retries and fallbacks aren’t enough to keep AI systems stable under real-world load. This guide breaks down how circuit breakers work, when to use them, and how to design for failure across your LLM stack.
How to identify and mitigate shadow AI risks in organizations using an AI Gateway
Shadow AI is rising fast in organizations. Learn how to detect it and use an AI gateway to regain control, visibility, and compliance.
What is shadow AI, and why is it a real risk for LLM apps
Unapproved LLM usage, unmanaged APIs, and prompt sprawl are all signs of shadow AI. This blog breaks down the risks and how to detect it in your GenAI stack.
LLM proxy vs AI gateway: what’s the difference and which one do you need?
Understand the difference between an LLM proxy and an AI gateway, and learn which one your team needs to scale LLM usage effectively.
Why enterprises need to rethink how employees access LLMs
Learn why self-serve AI access is critical for enterprise GenAI adoption, and how governed access with built-in guardrails helps teams innovate faster without compromising security or compliance.
Managing and deploying prompts at scale without breaking your pipeline
Learn how teams are scaling LLM prompt workflows with Portkey, moving from manual, spreadsheet-based processes to versioned, testable, and instantly deployable prompt infrastructure.