portkey-ai

portkey-ai

Portkey is a production-grade LLMOps platform and AI gateway for GenAI builders that provides a unified API to access 1,600+ LLMs, plus observability, guardrails, governance, prompt management, and caching to help teams deploy, monitor, and govern AI at scale.

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Free API 70/100
#417 in AI Agents (417 tools)
Added 0 year ago
Data reviewed Jul 15, 2026

Quick Overview

Best for: AI Agents

What it does

AI Agents software for decision-makers comparing workflow fit and alternatives.

Best fit

AI Agents

Pricing snapshot

Free

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portkey-ai

Portkey is a full-stack platform for putting generative AI into production. The product advertises an AI Gateway, observability and monitoring, guardrails and governance, prompt management, model catalog capabilities, and an MCP (Model Context Protocol) Gateway to centralize authentication, access, and observability of MCP servers. It targets developer and enterprise teams (trusted by Fortune 500s and startups) and emphasizes being production-ready, open source, and providing a unified API to access many LLMs.

Portkey positions itself to reduce integration overhead (access to 1,600+ LLMs via a unified API), provide real-time observability and audit logs, enforce network- and org-level guardrails and RBAC, and reduce cost through caching, routing strategies, and batching. The site offers SDK examples, documentation, demos, and claims SLAs and compliance (HIPAA compliant).

Portkey: AI control panel for observing, governing, and optimizing AI apps with AI Gateway and Observability Suite.

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Key Features

AI Gateway / Unified API

Access 1,600+ LLMs via a single, unified API so teams can build without managing many model integrations.

Observability

Real-time observability dashboard to monitor LLM behavior, catch anomalies early, and view detailed traces, errors, latency, and caching metrics.

Guardrails & Governance

Network-level guardrails, org-wide audit logs, RBAC, and governance controls to manage resources and ensure secure collaboration.

Prompt Management / Prompt Engineering Studio

Centralized prompt management to version, manage, and reuse prompts across teams and use cases.

Model Catalog

A catalog to manage available models and their configurations for teams to standardize model use.

MCP Gateway

Centralizes authentication, access, and observability of MCP servers so teams can build with MCP without maintaining infrastructure.

Caching & Cost Optimization

Intelligent caching, routing strategies, and batching to reduce AI expenses and provide measurable ROI.

PII Redaction

Automatic redaction of sensitive data from requests before they are sent to models to help secure user data.

SDKs & Plug-and-Play Integration

Client libraries and short code examples (Node.js, Python, OpenAI-style SDK) for quick integration; advertised "integrate in a minute" with 3-line examples.

Activity Logs & Audit

Track every action with detailed activity logs across resources to support monitoring and incident investigation.

Single Sign-On and Enterprise Onboarding

Single Sign-On support and enterprise onboarding capabilities to apply governance from day one.

Pricing

Free Tier Available

Get started for free (site offers a free getting-started option)

Use Cases

Production LLM Orchestration

Orchestrate multiple LLMs and route requests via the AI Gateway to provide reliable, production-ready agent workflows.

Observability and Debugging

Monitor model usage, latency, errors, and resource consumption in real time to debug and optimize LLM applications.

Governance and Compliance

Enforce RBAC, audit logs, PII redaction, and network guardrails to meet organizational and regulatory requirements.

Cost Control and Optimization

Apply caching, batching, and routing strategies to reduce inference costs and track spending per use case or team.

CI/CD & Developer Workflows

Cache repeated tests in GitHub workflows and integrate models into developer pipelines to avoid redundant costs and speed up development.

Integrations

Microsoft Azure

Cloud provider integration (build, deploy, manage)

MongoDB

Data storage and query integration; example guide: Portkey+MongoDB bridge

GitHub

Developer workflows and CI integrations (caching tests in GitHub workflows)

Docker

Container build and run integration for gateways and agents

Auth0

Authentication and identity provider integration

Figma

Design tool mentioned among integrations

Cloudflare

Security, acceleration, and delivery integration

Benefits

Faster time-to-market for GenAI applications through centralized LLM orchestration and easy integrations.
Reduced AI costs via caching, batching, routing strategies, and cost monitoring.
Improved security and compliance with PII redaction, RBAC, audit logs, and HIPAA compliance claims.
Unified visibility and monitoring across models and agents with detailed observability dashboards and logs.
Simplified developer experience with SDKs, short integration examples, and a single API surface for many models.

Limitations

Specific pricing tiers and per-unit model billing details are not provided on the supplied content.
Rate limit and API throughput details are not specified in the provided content.

Frequently Asked Questions

Claim this listing to publish FAQs.

Getting Started

  1. 1 Step 1: Sign up or Book a Demo (site links: "Book a Demo" / "Sign Up")
  2. 2 Step 2: View the docs and developer resources ("View the docs" is linked on the site) to configure the gateway and governance settings
  3. 3 Step 3: Integrate the SDK or API (example provided: 3-line Node.js/Python snippet) and begin routing requests through the Portkey AI Gateway

Support

docs

Developer documentation available on the site ("View the docs")

community

Community resources and links (site lists Community and GitHub with a community count and GitHub stars)

demo / sales

Book a demo option for enterprise onboarding and sales inquiries

status & changelog

API Status and Changelog links are listed on the site for operational visibility

API

Available: Yes
Documentation:

View the docs on the Portkey website (developer docs linked from the site)

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