The startup offers a software platform that enables users to ingest data and rapidly build, iterate, and deploy production-ready applications utilizing large language models. Its AI tool assists in debugging code and connecting to data sources, significantly reducing the time required to launch functional applications.
Funding
$1.6M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Organizations face challenges in managing and accessing a diverse range of large language models (LLMs) from different providers. This complexity leads to increased overhead in model integration, cost tracking, and ensuring consistent performance across various LLMs.
Solution
LiteLLM offers an LLM gateway and an OpenAI-compatible API that simplifies model access, spend tracking, and fallbacks across over 100 LLMs. The platform provides tools to control model access, track spending, and set budget limits across models, keys, and teams. It enables developers to easily migrate projects to the proxy via pass-through endpoints with built-in spend tracking and logging.
Target Audience
The primary audience includes platform teams and developers who need a unified interface to access multiple LLMs, track LLM usage, and set up guardrails.
Features
- LLM gateway to provide model access, logging, and usage tracking across 100+ LLMs
- OpenAI-compatible API for accessing various LLMs
- Logging and spend tracking to S3, Datadog, OTEL, Langfuse, etc.
- Model access control by virtual keys, teams, and model access groups
- Budget and rate limits across models, keys, and teams
- Pass-through endpoints for easy migration to proxy with built-in spend-tracking and logging
- Self-serve portal for teams to manage their own keys with SSO
- Support for virtual keys, budgets, teams, load balancing, and LLM guardrails