Cache and reuse your LLM outputs for near-instant responses, reduced costs, and consistent results.

Ensure the model’s responses always stick to your JSON Schema. No more missing fields or incorrect values, making your AI applications more reliable and robust.

Introducing the upgraded Claude 3.5 Sonnet and the new Claude 3.5 Haiku. The enhanced Claude 3.5 Sonnet offers comprehensive improvements, especially in coding and tool use, while maintaining the speed and pricing of the previous model. These upgrades make it an excellent choice for complex, multi-step development and planning tasks.

With the improvements to role-based access control (RBAC), it is much easier to assign and change workspace roles in Orq.

One common request we hear is whether it’s possible to attach files to an LLM — for example, to extract data from a PDF or engage with its content. With this update, you can now do just that.

The ‘Log Filters’ feature is now available, following high demand from our users. Monitoring logs is essential for tracking performance and identifying areas for improvement, and with this new feature, it’s now easier to find the exact data you need to make informed decisions.

Introducing Prompt Snippets, a feature designed to boost your efficiency by allowing you to reuse key parts of your prompt across multiple variants.

We’ve added a new Output Masking feature to further strengthen security for the most sensitive use cases. With this feature, you can now mask the entire model’s output in a Deployment, providing an additional layer of data protection.

We’ve added a new feature to the Billing page called Workspace Usage. This tool provides users with a clear overview of how many API calls they’ve used out of their available limit within their current billing cycle. The usage tracking starts from the beginning of your subscription.

Structured Outputs is a feature that makes sure the model's responses always follow your provided JSON Schema. This means you don't have to worry about the model leaving out any required parts or making up incorrect values.