Iryna Kondrashchenko & Oleh Kostromin

DataForce Studio

Build production AI without the friction of disconnected tools. DataForce Studio unifies the ML lifecycle with an open-source platform that runs on your own infrastructure.

DataForce Studio
#1about 1 minute

The hidden complexity of the machine learning lifecycle

Building a machine learning model is simple, but the full lifecycle including data prep, deployment, and monitoring makes production systems very difficult.

#2about 1 minute

Overcoming the fragmented machine learning tool ecosystem

DataForce Studio provides a set of well-integrated components to create a single, unified flow from model building to production monitoring.

#3about 1 minute

Using a model-centric design for a unified workflow

The platform defines a model as a standardized container with rich metadata, allowing all system components to work with it natively without extra configuration.

#4about 1 minute

Ensuring flexibility for diverse model types and use cases

The platform supports everything from traditional machine learning on tabular data to complex large language model pipelines and agent-based workflows.

#5about 1 minute

Avoiding vendor lock-in with an open-source platform

DataForce Studio is open source and uses a core module called Orbits, allowing you to bring your own storage and compute to maintain control over your data.

Related jobs
Jobs that call for the skills explored in this talk.

Featured Partners

From learning to earning

Jobs that call for the skills explored in this talk.