A centralized model-agnostic real time LLM evaluation & execution engine.

LLM, Cloud, 1st party, 3rd party agnostic, your Al Assistant for all GenAI use cases.

Grain Diagram

Code completion

Write code faster and more accurately with our code completion feature.

Chat

Have natural conversations with our AI chatbot, which can answer your questions and help you with your tasks.

Stable diffusion

Generate realistic images from text descriptions with our stable diffusion feature.

Text completion

Write text faster and more creatively with our text completion feature.

Join the waitlist

Be the first to try our new features and get early access to Grain.ai.

Use cases

  • Code completion
  • Text completion
  • Chat
  • Stable diffusion

Optimization criteria

  • Quality
  • Cost
  • Latency

Model selection

  • OpenAI
  • Anthropic
  • LLAMA
  • Grain Select
  • Your own model

Request a demo

About Grain.AI

Our mission is to unlock the collective potential of all Gen AI models. Our vision is to be a gateway to all Gen AI models and to generate the best and the fastest responses for any user and any prompt. Our immediate solution is a platform that calls any LLM and evaluates responses in real-time while reducing costs and improving quality.

Grain.AI is a gateway, a platform, and a tool to find, test, eval, and run any Generative AI model on the market. Grain.AI is a centralized and model agnostic Generative AI evaluation and execution platform. It is the only tool developers and users need to get started with generative AI. It continually adds new generative AI models allowing developers to easily explore and test models at scale in production and over time. The platform is model agnostic allowing developers to focus on the quality of model responses and outputs against both standardized and custom model evaluation queries (evals). evaLLM also allows organizations to create custom ensembles of models routing various requests to different models via a single API to get the best results regardless of which model generated the response, greatly simplifying the complexity of building software on top of generative AI models.

Log In