Introduction to AI Gateway

Monitor, Govern and Secure your AI traffic.

What is an AI Gateway?

An AI gateway is a middleware that acts as a unified access point to multiple LLMs, optimizing, securing, and managing AI traffic. It simplifies integration with different AI providers while enabling cost control, observability, and performance benchmarking. With an AI gateway, businesses can seamlessly switch between models, monitor usage, and optimize costs.

LangDB provides OpenAI compatible APIs to connect with multiple Large Language Models (LLMs) by just changing two lines of code.

Govern, Secure, and Optimize all of your AI Traffic with Cost Control, Optimisation and Full Observability.

What AI Gateway Offers Out of the Box

LangDB provides OpenAI-compatible APIs, enabling developers to connect with multiple LLMs by changing just two lines of code. With LangDB, you can:

• Provide access to all major LLMs Ensure seamless integration with leading large language models to maximize flexibility and power.

• No framework code required Enable plug-and-play functionality using any framework like Langchain, Vercel AI SDK, CrewAI, etc., for easy adoption.

• Plug & Play Tracing & Cost Optimization Simplify implementation of tracing and cost optimization features, ensuring streamlined operations.

• Automatic routing based on cost, quality, and other variables Dynamically route requests to the most suitable LLM based on predefined parameters.

• Benchmark and provide insights Deliver insights into the best-performing models for specific tasks, such as coding or reasoning, to enhance decision-making.

Quick Start with LangDB

LangDB offers both managed and self hosted versions for organisations to manage AI traffic . Choose between the Hosted Gateway for ease of use or the Open-Source Gateway for full control.

Quick Start

A full featured and managed AI gateway that provides instant access to 250+ LLMs with enterprise ready features.

Self Hosted

A self-hosted option for organizations that require complete control over their AI infrastructure.

Roadmap

• Prompt Caching & Optimization (In Progress) Introduce caching mechanisms to optimize prompt usage and reduce redundant costs.

• GuardRails (In Progress) Implement safeguards to enhance reliability and accuracy in AI outputs.

• Leaderboard of models per category Create a comparative leaderboard to highlight model performance across categories.

• Ready-to-use evaluations for non-data scientists Provide accessible evaluation tools for users without a data science background.

• Readily fine-tunable data based on usage Offer pre-configured datasets tailored for fine-tuning, enabling customized improvements with ease.