Oumi expands Frontier AI Engineer into agent development

Oumi has expanded Frontier AI Engineer beyond model-focused engineering into an end-to-end workflow for AI agents. The updated product covers building, evaluating, training, deploying, monitoring and continuously improving those agents.

The November 4 launch ties agent failures and production interactions to evaluation and post-training. Oumi says teams can turn those interactions into evaluation sets and training data, then use Frontier AI Engineer, or FAiE, to improve the models behind deployed agents.

Oumi says FAiE can help teams define an agent’s objectives, tools and operating environment; design evaluations; analyze failures; curate data; select models and training strategies; and run experiments. The workflow is meant to identify whether a failure stems from prompts, tools, orchestration or the underlying model before a team chooses a remedy.

Bring Your Own Harness is another part of the launch. Oumi says customers can keep their existing orchestration, tools, memory, environments and application logic while connecting those agents to its platform for evaluation, data curation and model training. Companies can therefore use the new training loop without rebuilding the software surrounding an agent.

For post-training, Oumi added direct preference optimization, or DPO, alongside its existing supervised fine-tuning support. DPO trains a model from examples of preferred behavior. Oumi also says teams can chain training methods in multistage workflows, with FAiE helping select strategies, design rewards, monitor training and diagnose problems.

Reinforcement learning through group relative policy optimization, or GRPO, is explicitly in private preview, and prospective users must request access. Oumi presents end-to-end agent development, Bring Your Own Harness, DPO and multistage training as launch capabilities without the preview qualifier. The company did not, however, provide separate availability dates or expressly label those features generally available. The announcement also did not disclose pricing, customer adoption figures or independent benchmark results.