About Portkey AI
What is Portkey AI?
Portkey AI is a full-stack LLM-ops platform designed to take generative-AI applications from experiment to production. It offers a universal API gateway through which users can access 1,600+ LLMs across providers, with features such as smart routing, load-balancing, fallback, caching and retries. Running on an enterprise-grade infrastructure, it includes real-time observability (logs, traces, metrics) for AI workflows, a prompt-management studio (versioning, collaboration, A/B testing), built-in guardrails and governance (PII redaction, schema validation, RBAC, audit logs), and support for agent frameworks and multimodal models. Backed by a vibrant open-source community, the platform serves thousands of GenAI teams globally and supports seamless integration into existing stacks. The company was founded in January 2023, and has raised seed funding to scale its LLM-OPS capabilities. Use-cases include enabling organisations to launch AI features faster with full visibility, cost-control and enterprise-grade reliability.
How to use Portkey AI?
To get started with Portkey AI, visit their website and create an account. Once you're set up, explore features like AI Gateway & Multi-Provider Support, Observability & Monitoring, Prompt Management Studio.
What Are the Key Features of Portkey AI?
Access 1,600+ large language models via a unified API with conditional routing, automatic retries, load-balancing, caching and multimodal support.
Provides real-time logging, tracing and metrics of LLM API usage (token usage, latency, errors, model drift) so teams gain visibility into AI workflows.
A central library for prompts with version control, templating, A/B testing and deployment across models, enabling teams to iterate and scale prompt engineering effectively.
Built-in policies and guardrails (e.g., PII masking, schema validation, content moderation), role-based access control (RBAC), audit logs and compliance support for enterprise AI governance.
Semantic caching, request deduplication and intelligent routing reduce token spend and latency for repeated or similar queries.
Integrates with popular agent frameworks (LangGraph, CrewAI, etc.) and supports workflows across text, image and audio models, enabling richer AI applications.