AI tool sprawl creates fragmented access, inconsistent governance, and rising operational overhead. This guide explains why it happens, the risks it introduces, and practical steps teams can take to bring structure back to their AI stack.
ai gateway
A concise comparison of Gemini 3.0 and GPT-5.1 across reasoning, coding, multimodal tasks, agent performance, speed, and cost. Learn which model performs better overall and how teams can run both through a single production-ready gateway.
ai guardrails
Qualifire is partnering with Portkey, combining Portkey's robust infrastructure for managing LLM applications with Qualifire's specialized evaluations and guardrails
MCP
Releasing November 25, the latest MCP update introduces async operations, stateless architecture, and registry GA, advancing MCP from a standard to an interoperable ecosystem for production AI systems.
anthropic
A detailed look at Claude Skills — what they are, how they work, and why they matter. Learn how Anthropic’s new Skills framework could make LLM workflows more structured, consistent, and efficient for real-world use.
Agents in Production
Multi‑agent evals are powerful but hard to debug. Portkey’s trace visualization let us pinpoint failure paths (one case took 38 LLM calls over 12 minutes) and drove massive quality and accuracy lifts while cutting time‑to‑issue detection in half.
Learn how to build complete LLM observability, from tracing and guardrails to cost and governance with frameworks and examples from Portkey.
Multi‑agent evals are powerful but hard to debug. Portkey’s trace visualization let us pinpoint failure paths (one case took 38 LLM calls over 12 minutes) and drove massive quality and accuracy lifts while cutting time‑to‑issue detection in half.
AI observability has evolved. Learn what defines the best AI observability tools today and how Portkey, recognized in 2025 Gartner® Cool Vendors™ in LLM Observability, delivers a complete stack to run AI in production.
The recent announcement of the official MCP Registry is a significant milestone, signaling a new phase of maturity for the AI ecosystem. It provides a much-needed standard for public server discovery and is a welcome development. For enterprise CIOs and platform leaders, however, this announcement should be seen not as
Discover how the Prisma AIRS integration with Portkey combines industry-leading AI security with comprehensive observability.
Reports, Benchmarks, and Guides on Putting LLMs in Prod
AI observability has evolved. Learn what defines the best AI observability tools today and how Portkey, recognized in 2025 Gartner® Cool Vendors™ in LLM Observability, delivers a complete stack to run AI in production.
How Opentelemetry's semantic conventions enable rich analytics on Portkey
Teams are quickly prototyping use cases with LLMs: automating claims summaries, extracting information from documents, or assisting member support. Explore the fastest way to give every team safe, secure access to LLMs, without losing observability, governance, or control.
As GenAI moves from experiments to production, LLM observability is becoming a business-critical function, driving reliability, governance, and trust in enterprise AI systems.
Compare GPT-5 Nano and Claude Haiku 4.5 across reasoning, coding, and cost. See which lightweight model fits your production stack and test both directly through Portkey’s Prompt Playground or AI Gateway.
How Syngenta introduced AI gateways to 100 employees through a company-wide hackathon, combining secure access, model governance, and hands-on experimentation.
Learn how to connect OpenAI AgentKit workflows with multiple LLM providers and get observability, guardrails, and reliability controls.
Portkey’s AI Gateway delivers enterprise-grade reliability at scalw. Learn how configurable routing, governance, and observability makes Portkey the most reliable AI gateway for production.
Managing multiple LLMs meant juggling auth, errors, and APIs. Instead of managing APIs, I chose Portkey's AI gateway to handle the infra, so I could build Dictation Daddy!
A head-to-head comparison of Claude Sonnet 4.5 and GPT-5, covering coding, reasoning, math, tool use, cost, and ecosystem integrations , with insights on where each model is best suited for enterprise use.
Enterprises need both speed and security when taking AI to production. Learn more about challenges of AI adoption, the role of guardrails, how AI gateways operationalize them at scale.
This guide provides a complete reference for every MCP message type, with real JSON examples you can use in your implementations.