FAiE

FAiE (Frontier AI Engineer) is the flagship agent from enterprise AI platform Oumi. In its 2026-11-04 Fall Launch, Oumi extended FAiE from model training into end-to-end agent development: describe a goal in plain language and FAiE helps define tools and environments, design evaluations, curate data, pick training strategies, deploy, and turn production failures into new evals and training sets.

New pieces include Bring Your Own Harness (keep your orchestration/tools/memory; connect Oumi for eval and training), DPO, and GRPO reinforcement learning in private preview. Docs live at docs.oumi.ai.

What problem it solves

Agent failures may come from prompts, tools or the underlying model. Most teams only tweak prompts/harnesses because weight updates are hard. FAiE aims to automate the AI-engineer loop from goals through retraining.

Capabilities

• Dataset synthesis, evaluators/evals, training, deployment and failure-mode analysis.
• Multi-stage training: SFT → DPO → GRPO (preview) can be chained.
• Costly or side-effectful actions require explicit approval cards.

Limits

• Enterprise SaaS, not an open-source local tool.
• GRPO remains private preview.
• Does not replace file uploads, Playground runs, or billing/key management.

Who it's for

• Enterprise teams building and continuously improving specialized agents;
• Platform groups with an existing harness that want unified eval and training.

Getting started

1. Read the Fall Launch page and FAiE docs.
2. Create a project in Oumi and ask FAiE in natural language to plan evals and training.
3. If you already have a harness, connect it via Bring Your Own Harness.
4. Request GRPO private preview when you need RL against task outcomes.