Oumi Launches the Agent That Builds, Trains, and Continuously Improves AI Agents

Oumi, the enterprise AI platform for building and owning specialized intelligence, announced end-to-end, AI-automated agent development. Powered by FAiE (Frontier AI Engineer), Oumi enables enterprises to build, evaluate, train, deploy, and continuously improve AI agents. Teams can build agents directly in Oumi or connect their existing agent infrastructure for evaluation, data curation, and model training.

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Building AI agents is easy. Making them reliable is hard. Until now.

When agents fail, teams must determine whether the problem lies in prompts, tools, orchestration, or the underlying model. Traditionally, enterprises have relied on prompt and harness engineering, often hitting their limits before achieving the required reliability. Training the model weights behind agents, especially using advanced techniques from frontier AI labs, has required specialized expertise and significant effort, making it prohibitive.

Oumi closes this gap by unifying agent development and model training in a continuous improvement loop. Teams can evaluate agent behavior, diagnose failures, and turn production interactions into evaluation sets and training data to improve the models powering their agents.

Meet FAiE: The AI Engineer That Improves Your Agents

At the center is FAiE, Oumi’s AI agent that automates AI engineering. FAiE helps define objectives, design evaluations, analyze failures, curate data, select models and training strategies, and execute experiments. Now extended to agent development, FAiE helps teams define tools and environments and systematically train the models behind their agents.

Enterprises can describe what they want their agents to accomplish and let FAiE automate the engineering work, with full transparency, flexibility, and control.

“Building AI agents is easy. Making them reliable is the next frontier,” said Manos Koukoumidis, co-founder and CEO of Oumi. “The best agents won’t just rely on better prompts, expanded harnesses, or bigger generic models. They’ll improve by training the weights of the models powering them, learning from their own work: where they failed, what users preferred, and whether they completed the task. With FAiE, every enterprise gets an AI engineer to automate that training and continuously improve the intelligence behind its agents.”

What’s New In This Launch

• End-to-End Agent Development: Build, evaluate, train, deploy, monitor, and continuously improve agents in one platform. Turn production failures into evaluation sets and training data.
• Bring Your Own Harness: Keep existing orchestration, tools, memory, environments, and application logic while connecting to Oumi for evaluation and model training. Improve models within the environments where agents operate.
• Advanced Post-Training: Building on existing supervised fine-tuning (SFT), Oumi introduces direct preference optimization (DPO) to train models on preferred behaviors and reinforcement learning through GRPO (Private Preview) to optimize models against task outcomes. FAiE helps select strategies, design rewards, monitor training, and diagnose problems.
• Multi-Stage Training: Chain together different training methods to support more advanced model development workflows.

From Renting Intelligence to Owning Intelligence That Improves

Most enterprise agents rely on generic models that aren’t optimized for their specific tasks. Oumi enables enterprises to build and own specialized models with the potential for higher quality, lower cost, and greater control.

By connecting agent outcomes directly to model training, enterprises can turn their agents’ experiences into proprietary intelligence that compounds over time.

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