Enabling AI transformation through MLOps
We help companies
to develop MLOps
(Machine Learning Operations)
on Azure, AWS and Google Cloud
We provide consultancy services on MLOps
We help your business automate and accelerate
the machine learning lifecycle
Multicloud
Most of our clients want solutions on
Azure, AWS and Google Cloud.
However, we also develop using
other cloud providers and on-premise.
CI/CD Pipelines
Continuous Integration and
Continuous Delivery (CI/CD)
of ML models is key for managing
end to end AI workloads.
Reproducible ML
Creating repeatable and reproducible pipelines
helps to improve control over data preparation,
training and scoring processes.
ML Deployment
We help you to deploy ML models in production
faster, maintaining high quality and security.
ML Monitoring
We help you monitor ML models in production
and analyze your business metrics
through techniques like A/B testing.
Data Governance
We help you track the lifecycle
of the ML deployments
by versioning and profiling your data.
Our Technologies
Our expertise covers multiple areas of Machine Learning and Deep Learning
Natural Language Processing
Analyzing, understanding and generating language, both written and spoken.
Recommendation Systems
Learning users' interests according to their historical behaviors to predict preferences for a given item and reduce information overload.
Computer Vision
Automatic understanding, analysis and extraction of useful information from images and videos.
Time Series Forecasting
Analysis of temporal series to extract meaningful characteristics and predict future values based on past data.
Reinforcement Learning
Type of machine learning aimed to take optimal decisions, without human intervention, based on rewards.
Knowledge Representation
Representing information in a form that can be used by a computer to solve complex tasks, reason and create inference engines.
Excited To Start
Your Next Project?
Case Studies
Successful projects, happy customers, great results
