Emmanouil Koukoumidis
CEO
Oumi
Oumi provides an AI-native platform that automates the entire lifecycle of custom model development—from failure analysis and synthetic data generation to fine-tuning and one-click deployment. The platform enables organizations to build specialized models that can match or exceed frontier AI performance on specific tasks while reducing inference costs by up to 100x and retaining full ownership of model weights and data.
- Artificial Intelligence
- Developer Tools
- Software Only
- Enterprise Software
Updated 1 month ago
Funding
Raised to date
$10MRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
across 1 round
1LAV$10M · Seed
Announced Jan 2025
Disclosed cumulative: $10M
RoundDateAmountValuationInvestors
Founders
Product
Problem
Organizations relying on off-the-shelf foundation models face high inference costs, vendor lock-in, and slow iteration cycles, making it difficult to tailor AI to specific domain needs or maintain control over data and model updates. General-purpose frontier models are often too large, too expensive, and not specialized enough for production workloads in regulated industries like banking, insurance, and healthcare.
Solution
Oumi provides an AI-native custom model development platform that automates the full lifecycle—from failure analysis and synthetic data generation to automated fine-tuning and one-click deployment. By starting from a single prompt, the system evaluates failure modes, synthesizes training data without a dedicated annotation team, and trains models automatically, delivering custom models that match or exceed frontier performance on specific tasks at a fraction of the cost. Users retain full ownership of model weights and data lineage, eliminating deprecation risks and pricing surprises. The platform supports local, cloud, or hybrid deployment, continuous drift monitoring, and rapid re-training on new open-weight releases, ensuring models improve over time while remaining under the user's control. Oumi describes itself as "your AI Factory production line" that "builds, deploys, and continuously improves your AI to your advantage," with specialized models being 10x to 100x smaller than frontier AI while matching or exceeding performance on specific tasks.
Target Audience
Primary customers are ML engineers, data scientists, and research teams in enterprises or academic institutions that need production-grade, domain-specific models while retaining full control over their AI assets. The platform targets regulated industries including banking, financial services, insurance, healthcare, retail, and SaaS, with pre-built use cases like support resolution, fraud detection, claims coverage, clinical trial matching, and loan approval.
Features
- Automated evaluation pipeline that identifies and ranks failure modes with concrete examples
- Zero-annotation data synthesis that converts failure analyses into high-quality training sets
- Prompt-driven fine-tuning that runs end-to-end without manual labeling or extensive engineering (SFT, LoRA, QLoRA, DPO, GRPO)
- One-click deployment to any inference provider with built-in drift detection and feedback loops; deploy to Oumi's GPUs that scale to zero when idle, or to your own VPC, on-prem, or edge devices
- Full ownership of model weights, data lineage, and improvement cycles; no vendor-imposed deprecation
- Open-source OSS stack supporting pre-training, fine-tuning, hyperparameter tuning, and multi-node cloud training across AWS, GCP, Azure, and Lambda Labs
- The compounding flywheel: production signals feed back into training automatically, turning failure modes into training data that retrains on a cadence you control
- Transparent pricing per token, GPU hour, and model size; free tier and pay-as-you-go options