Klu

What is Klu?

Klu is an all-in-one LLM App Platform designed to help AI Engineers and teams build, deploy, and optimize Generative AI applications. It provides tools for collaborative prompt engineering, automatic evaluation of prompt and model changes, 1-click fine-tuning of models, and seamless integration with various data sources (databases, files, sites) and best-in-class LLMs (Claude, GPT-4, Llama 2, Mistral, Cohere, etc.). Klu aims to enable rapid iteration, understand user preferences, and curate data for custom models, ultimately helping businesses create unique AI experiences and competitive moats.

How to use Klu?

Users can start for free to build and evaluate generative features. The platform allows teams to collaborate on prompts, prototype completions and workflows, track changes, and integrate into product development. It provides automatic evaluation of prompt and model changes, and enables 1-click fine-tuning of models. For deployment, users can host models in their own cloud using Klu Enterprise Container or utilize the self-hosted core platform.

Klu’s Core Features

Collaborative prompt engineering (explore, save, prototype, track changes) Automatic evaluation of prompt and model changes 1-click fine-tuning of LLMs (GPT-4, Llama 2, Mistral, etc.) Integration with various best-in-class LLMs (Claude, GPT-4, Llama 2, Mistral, Cohere, etc.) Seamless data integration with databases, files, or sites Rapid iteration with usage and system performance insights Data curation for fine-tuning custom models Klu Enterprise Container for private cloud deployment Self-hosted core platform option A/B Experiments, Change Versioning, Deploy Environments Secure and portable data

Klu’s Use Cases

• Developing chatbots with seamless integration into platforms like WhatsApp.
• Addressing data privacy, regulatory compliance, and security concerns for Enterprise clients adopting LLMs.
• Building AI features for products, such as automatic issue suggestions or summarizing feedback.
• Creating unique AI experiences and performance through fine-tuning custom models.
• Personalizing software products to individual users and helping them accomplish tasks faster.