Retune

The platform positions itself as the missing infrastructure layer between raw AI model capabilities and the custom AI applications that businesses and developers want to deploy, providing the data connection, configuration, and deployment tooling that transforms a general-purpose language model into a purpose-specific assistant trained on an organization's unique knowledge and requirements.

Data source connectivity is central to Re:tune's value proposition.

Chatbots built on the platform can be trained with virtually any structured or unstructured data source uploaded documents, databases, web scraped content, API responses, and proprietary knowledge bases allowing the resulting AI to answer questions, generate responses, and take actions informed by specific organizational context rather than general training data alone.

This data connection capability is what transforms a generic AI chatbot into a custom customer support agent that knows a company's products, or an internal assistant that understands a team's workflows and documentation.

The choice between frontier models reflects Re:tune's recognition that different use cases call for different model characteristics. GPT-4 provides exceptional reasoning capabilities for complex multi-step tasks and nuanced content generation.

Claude offers an impressively long context window that enables working with very long documents, extended conversation histories, and complex multi-document synthesis. GPT-3.5 delivers fast, cost-effective responses for high-volume, straightforward query handling.

Re:tune users can select and switch between these models based on the performance and cost profile their specific application requires.