Easy-to-use, exclusive 🤗HuggingFace as a Marketplace.

Home of exclusive AI

A unique marketplace that provides both inference and training for only exclusively business-tailored AI models.

The short video pitching our idea.

You can visit the ML-Hub.

What is the problem

People are getting lost among the tons of pre-trained AI models that both serve on APIs and sit idle on GitHub repositories. Additionally, the amount and variety of domain-specific pretrained models such as Healthcare, Legal and Finance are very limited. Seeking out the best model for your needs among those models and discovering and connecting to the right API are very difficult and time consuming as each API has its own network protocols, structure, documentation and data format.


ML-Hub allows us not only to monetize the idle pre-trained models but also to host only state of the art models by providing a competitive environment so it saves you from getting lost among models.

We bring the world’s best (accuracy + speed + security + users’ feedback) AI models together and make them available to developers/enterprises in one place. We will make it happen with the exclusive models trained by not only the ML-hub team but also our community.

Our marketplace allows developers to discover, test, and integrate various AI related APIs. Developers can see the demo of the API, play with them right from their browser, subscribe to the API, and then integrate one by copying a simple code snippet.

Business Values

Comparison with the Hugging Face
Do model uploaders earn money from their exclusive SOTA models?


API-based Repo


API-based Marketplace

Do users seek out the best models fast and easily?


Hard to choose right one among overcrowded models


Only proven models accepted

Are there sufficient business-tailored models to use?


Lack of domain-specific models such as Healthcare, Legal and Finance.


Primary focus area : Domain-specific SOTA models

Competitive Advantages

Business-tailored exclusive models

  • Quality of our AI models comes from both the wisely-use of transfer learning and also data labeling capability.

For example :

De-identification of Personal Health Information (PHI) from medical records is one of the highly-challenging domain-specific NER (Named Entity Recognition) tasks. Our model outperforms current SOTA by %10 on the i2b2 official de-identification test data.

Unique infrastructure for model training and inference.

  • Our infra is established on exclusive ML-Ops technologies such as Kubernetes, Kubeflow, Kserve.
  • AI models will be able to run not only on the desired cloud platform but also on customers’ private servers.
  • We offer minimum latency and scalability of model inference.
  • Thanks to our unique infra, low prices will become inevitable.

We will save you from getting lost among thousands of AI models on the market.

  • Based on the leaderboard approach we will develop, only a certain number of SOTA AI models will be able to serve. In this way, we will both keep the quality at the highest level by encouraging competition and also the idle AI models in the repos will make money.


To become the market leader with a 30% market share in the domain-specific AI Marketplace in two years.

Who We are?

We are a group of passionate instructors and mentors coming from a wide range of IT disciplines with deep industry experience who founded the online IT bootcamp company “Clarusway”. We have started the ML-Hub project with the encouragement of 92% job placement success of our graduates in the USA in a short period of two years, including best companies such as Apple, IBM, Ebay, Infosys and AWS.

Core Team

J.Murat G.- MSc

ML-Hub Lead

Russell C.- MSc

ML Engineer Lead

Joe B. - PhD (Industrial Engineering)

Project Manager

Armando R. - MSc

DevOps/MLOps Team Lead

Raife H.

NLP Engineer Lead

Bunyamin K.- PhD (Healthcare Management)

Annotation Team Lead

Zahire S.- PhD (Mathematics)

CV Engineer Lead

Forest F.

Data Engineer Lead



Furkan O.

DevOps Engineer

Aaron S.

Software Engineer Lead


Serdar Gümüs - PhD (Mathematics)

Dev. Sec. Ops. at Ebay

Emirhan Bozdoğan

Data Analyst at IBM

Ayhan D.

Dev.Ops.Software Engineer at Bank of America


Nuray Yurt - Ph.D. (Pharma-Biotech Leadership)

Head of AI Solutions at Novartis Oncology

Market Size

Financial Goal




Use of Funds

Cloud infrastructure cost both in development and production.

Hiring cost of engineers and domain experts.

Marketing and Sales cost.

Our business model is based on the fees we receive from our customers based on both B2B and B2C