We’ve enhanced our fallback and retry system to provide even greater reliability and flexibility in production use cases. Previously, Orq.ai allowed users to define a single fallback model if the primary model failed to generate a satisfactory output. Now, we’ve increased the number of fallback models to five, giving users even more control over model orchestration without additional coding.

We’ve introduced a new feature that makes it easier than ever to reuse your prompts within Orq.ai. With the import functionality, you can seamlessly integrate your already created, version-controlled prompts into your Playgrounds, Experiments, and Deployments.

We've made a significant update to how datasets work in Orq.ai with the release of Datasets v2. This update merges variable collections into datasets, streamlining the structure and eliminating confusion between the two concepts.

We’re excited to introduce Experiments V2, a major upgrade to our Experiments module that makes testing, evaluating, and benchmarking models and prompts more intuitive and flexible than ever before.

We are excited to announce the integration of DeepSeek’s latest AI models—67B Chat, R1, and V3—into our platform.

Start using OpenAI’s newest and most advanced ‘small’ reasoning model: o3-mini.

Experience the power of the latest Llama 3.3 70b and Llama Guard 3 models on Orq, integrated via Together AI.

We’re introducing a new project structure UI to help you organize and manage your resources more effectively. With projects, you can group your work by use case, environment, or any logical structure that suits your needs.

You can now configure Guardrails after you have added them to your Library directly in Deployments > Settings for both input and output, giving you full control over live deployments.

You can now add HTTP and JSON Evaluators and Guardrails under the Evaluator tab and add them to your Deployment or Experiment.