MLOps platform

GRACE is the platform for model lifecycle management & integration

Efficiently develop, deploy, operate and integrate models into your existing IT infrastructure.

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A platform lowers the barrier of entry and enables fewer engineers to reinvent less, allowing them to focus on implementing AI that is specific to the business.

Danny Lange, Board Member & SVP at Unity Technologies

Increase efficiency with GRACE on your team

GRACE offers your Data Science and IT team efficient workflows. With full transparency and monitoring of activities across all ML projects, your team can focus resources on tasks like data ingestion, feature extraction, and model development, while GRACE maintains the required surrounding infrastructure.

GRACE for Data Science

As a Data Scientist, you want the freedom to build models using the open-source components you trust. With GRACE, you have the flexibility to do so and a platform that reduces the manual engineering work required.

Data source catalog

Tabular, text, video, image

Ingest from any data source

Data connectivity with code

Dash apps

Python and R libraries

Notebooks

Multi-projects and models

Model performance logging

R & Python

GPU/CPU

Docker-based deployment

Pipeline supported model runs

Load balanced APIs

Horizontal scalability (scaling to zero)

GRACE for IT operations

With GRACE, you get the tools to manage models in production efficiently. From monitoring dashboards to alarms and re-training schedules, GRACE makes your IT operations for models straightforward.

One-click deployment

Horizontal scaling

Kubernetes pipeline builder

Image, video, and NLP supported

Application builder

Secure APIs

Endpoint management

Metrics logging

Dashboarding

PDF exporting of model stats

Usage stats

IT Operations dashboard

DS and IT KPIs

Infrastructure cost control

MLOps monitoring

GRACE for digitization of AI project management

GRACE is the digital partner to connect stakeholders across your organization for all AI projects. You manage the roles and operate within one platform rather than multiple single software components, which increases operational efficiency and reduces risk.