Portkey vs OpenLIT Detailed comparison features, price

Portkey

Portkey offers a robust suite of tools designed to streamline AI application development and deployment. Through its advanced AI Gateway, teams can access over 200 LLMs via a single endpoint, implementing essential features like fallbacks, load balancing, and caching.

The platform combines powerful observability tools, providing insights from 40+ metrics, with sophisticated guardrails for reliable LLM behavior. Its integration capabilities extend to major agent frameworks like Langchain, CrewAI, and Autogen, while maintaining industry-standard security certifications including SOC2 and HIPAA compliance.

OpenLIT

OpenLIT is a comprehensive open-source platform designed to simplify and enhance AI development workflows, with a particular focus on Generative AI and Large Language Models (LLMs). The platform provides essential tools for developers to experiment with LLMs, manage prompts, and handle API keys securely while maintaining complete transparency in its operations.

At its core, OpenLIT offers robust features including application tracing, cost tracking, exception monitoring, and a playground for comparing different LLMs. The platform integrates seamlessly with OpenTelemetry and provides granular insights into performance metrics, making it an invaluable tool for organizations looking to optimize their AI operations while maintaining security and efficiency.

Portkey

Pricing

Freemium

From 49$

OpenLIT

Pricing

Other

Portkey

Features

AI Gateway: Route to 200+ LLMs with single endpoint integration
Observability Suite: Monitor costs, quality, and latency with 40+ metrics
Guardrails System: Enforce reliable LLM behavior with synchronous checks
Prompt Management: Collaborative prompt development and deployment
Agent Integration: Production-ready workflows with major agent frameworks
MCP Client: Access to 1000+ verified tools for AI agents

OpenLIT

Features

Application Tracing: End-to-end request tracking across different providers
Exception Monitoring: Automatic tracking and detailed stacktraces
LLM Playground: Side-by-side comparison of different LLMs
Prompt Management: Centralized repository with versioning support
Vault Hub: Secure secrets and API key management
Cost Tracking: Monitor and analyze usage expenses
Real-Time Data Streaming: Low-latency performance monitoring
OpenTelemetry Integration: Native support for observability

Portkey

Use cases

AI Application Development
LLM Implementation Management
Enterprise AI Operations
AI Performance Monitoring
Prompt Engineering and Deployment
AI Agent Development

OpenLIT

Use cases

Comparing performance of different LLMs
Managing and versioning AI prompts
Monitoring AI application performance
Securing API keys and sensitive data
Tracking AI implementation costs
Debugging AI applications
Optimizing LLM performance

Portkey

FAQs

How does Portkey work?

Portkey works by replacing the OpenAI API base path in your app with Portkey's API endpoint, which then routes all requests to OpenAI while providing control and management capabilities.

How do you store my data?

Portkey is ISO:27001 and SOC 2 certified, GDPR compliant, and encrypts all data in transit and at rest. For enterprises, they offer managed hosting in private clouds.

Will this slow down my app?

No, Portkey actively benchmarks for latency and may improve app experience through smart caching, automatic fail-over, and edge compute layers.

OpenLIT

FAQs

How does OpenLIT handle security for sensitive data?

OpenLIT provides a Vault Hub feature that offers secure storage and management of sensitive application secrets, with secure access methods and environment variable integration.

What kind of monitoring capabilities does OpenLIT offer?

OpenLIT offers comprehensive monitoring including application tracing, exception monitoring, cost tracking, and performance metrics with OpenTelemetry integration.

How does the prompt management system work?

The prompt management system provides a centralized repository where users can create, edit, and version prompts, supporting major, minor, and patch updates, with dynamic variable substitution using {{variableName}} convention.