Unify AI provides a platform for developers to manage and assign tasks to various Large Language Models (LLMs). It abstracts the complexity of integrating different AI APIs, allowing users to focus on task execution rather than model selection. The service aims to simplify the deployment and management of AI workflows across different models.
Funding
$8M 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.
+8Founders
Product
Problem
Developing applications with Large Language Models (LLMs) requires careful consideration of factors like cost, speed, and accuracy, making it challenging to select the optimal model for a specific task. Developers often lack the tools to objectively compare and benchmark different LLMs across various providers.
Solution
Unify offers a platform that simplifies LLM selection and deployment by providing tools to benchmark, evaluate, and route requests to the best model for each specific use case. The platform's core component is a learned neural network router that intelligently directs requests based on performance, cost, and quality requirements. By offering a unified API to access multiple LLM providers, Unify enables developers to optimize their AI applications without being locked into a single model or vendor. The platform also provides features for logging, evaluation, and the creation of custom interfaces, allowing for continuous improvement and adaptation to changing requirements.
Target Audience
Unify targets AI developers and engineers who are building and deploying LLM-powered applications and need tools to optimize performance, cost, and quality across different models and providers.
Features
- LLM router that optimizes for quality, cost, and speed using a learned neural network
- Unified API for accessing multiple LLMs across various providers (e.g., OpenAI, Mistral AI, Anyscale)
- Live runtime benchmarks and dashboards for comparing LLM performance
- Tools for building custom interfaces for logging, evaluations, and guardrails
- Support for building custom benchmarks to evaluate LLMs on specific tasks
- Integrations with popular tools and frameworks for LLM development
- Observability features for monitoring and analyzing LLM application performance