AI command center for your product.

Semantic caching, model fallbacks, rate limiting user, logging & analytics, A/B testing — all in one place, in minutes.

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Reduce your LLM costs by 10x using semantic caching.

Decrease your LLM expenses by 10x & improve speed by 100x. We employ embedding algorithms to convert queries into embeddings and uses a vector store for similarity search on these embeddings.

Improve reliability of your requests with model fallbacks.

If your LLM model fails, our platform will automatically fallback to a different model to ensure that your users are never left without a response.

Rate limit your users to prevent abuse.

Our platform allows you to rate limit your users to prevent abuse. This can help you to protect your LLM from being overloaded by malicious users.

Get real-time insights into your LLM usage.

Our platform provides insights into your LLM usage, including the number of requests made, the latency of requests, and the cost of requests. This information can help you to optimize your LLM usage and save money.

A/B test your LLM models with ease. (WIP)

Quickly test different LLM models and prompts to find the best combination for your use case. Our platform makes it easy to set up A/B tests and track the results.

Call over 100+ supported providers using the OpenAI format

Our platform supports over 100+ providers, including OpenAI, TogetherAI, VertexAI, Huggingface, Bedrock, Azure, etc. We are OpenAI compatible so you have to make minimal changes in your code.

import { OpenAI } from "openai"

// Initialization
const openai = new OpenAI({
  baseURL: "https://www.ultraai.app/api/v1",
  apiKey: "<PROJECT_API_KEY>"
})

// Usage
const completion = await openai.completions.create({
  model: "<PRESET_KEY>",
  prompt: "hello! how are you?",
  stream: true,
  user: "<USER_ID>" // optional, for rate limiting
})
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