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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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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Claim this listing for $29Key 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
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
Limitations
Frequently Asked Questions
Claim this listing to publish FAQs.
Getting Started
- 1 Step 1: Sign up or Book a Demo (site links: "Book a Demo" / "Sign Up")
- 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 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
View the docs on the Portkey website (developer docs linked from the site)
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