Latest

LLM Deployment Pipeline Explained Step by Step

Everything you need to deploy LLMs in production – inference frameworks, serving layers, scaling strategies, monitoring, and cost management.

How to host an AI Hackathon without losing control of your keys or budget

Running an AI hackathon means providing dozens (or hundreds) of teams with access to expensive LLM APIs while maintaining cost control, fair usage, and visibility into what's happening. Without proper infrastructure, you risk: - Budget blowouts: A single runaway script consuming your entire API budget- - - No

The best approach to compare LLM outputs

Once LLMs are in production, output quality stops being a subjective question and becomes an operational one. Teams are no longer asking whether they need to evaluate outputs, but how to do it reliably as systems evolve. Production systems can change frequently. Prompts are iterated on, models are swapped, routing

OpenAI Responses API vs. Chat Completions vs. Anthropic Messages API

A side-by-side comparison of OpenAI's Chat Completions, Responses API, and Anthropic's Messages API, covering key differences, use cases, and how to avoid vendor lock-in with Portkey.

Portkey Raises $15M Series A to Scale the Unified Control Plane for Production AI.

Our latest raise enables us to scale the infrastructure layer enterprises need to run AI reliably and accountably Today we're proud to announce Portkey has raised $15 million in Series A funding led by Elevation Capital, with participation from Lightspeed. This investment reflects the industry-wide shift we'

Securing the MCP Gateway: Lasso Partners with Portkey to Deliver Enterprise-Grade Agentic AI Protection

Today, we’re excited to announce that Portkey and Lasso Security have partnered to provide AI Security directly into Portkey’s MCP Gateway - delivering real-time guardrails, threat detection, and governance enforcement at the protocol level.  Portkey's MCP Gateway serves as the operational control plane for MCP deployments,

Introducing the MCP Gateway

Your interns need three approvals to touch production. Your AI agents? Zero. With MCP, agents can take real action – connect to databases, trigger workflows, access internal systems. The protocol just works. But here's what we kept hearing from teams actually running MCP in production: "How do I

We Tracked $93M in LLM Spends Last Year. Now the Data is Yours.

Accurate pricing for 2,000+ models across 40+ providers. Free API, no auth required.

How Fontys ICT built an institutional AI platform with a gateway architecture

Fontys ICT shares how it built a governed, multi-provider AI platform using a gateway architecture to ensure equitable access, EU compliance, and cost control.

LLM hallucinations in production

Hallucinations in LLM applications increase at scale. This blog explains how AI gateways and guardrails help control, detect, and contain hallucinations in production systems.

OpenCode: token usage, costs, and access control

A practical guide to managing OpenCode token usage, costs, and governance in shared or production environments.

MCP tool discovery for autonomous LLM agents

A concise summary of the MCP-Zero paper, explaining how active tool discovery enables scalable, autonomous LLM agents while reducing context overhead.

Enterprise MCP access control: managing tools, servers, and agents

Learn how MCP access control works and how enterprises can govern MCP tools and agents safely in production environments.

What is a virtual MCP server: Need, benefits, use cases

As teams use more MCP servers, virtual MCP servers help simplify provisioning by combining tools into a single interface. See how they help, and use cases.