If data science touches your workflow, you maybe interested to subscribe.
Learn how using opsmate could be a game changer for ensuring ROI on your AI layer.
Organisations are now building machine learning models to solve various business problems. Many of the use-cases focus on learnings from historical data and require re-training as soon as new data is available, which may be occurring recurrently. We help such organisations re-train and deploy models at scale with the ability to choose their infrastructure, platform and tool choices.
Specific use-cases such as fraud detection, network security, genomic sequencing and ad re-targeting would focus on instant processing with low latency, so as various integrated systems can take actions almost in real-time. We help organisations build custom machine learning pipelines to consume, process and send data instantaneously.
Learn what makes our product unique!
Models deployed in production can be re-trained by triggering or scheduling on data or model change.
We support highly scalable and available web-service generation from pre-trained models.
Easy to use interface to split traffic between different deployed model version. Ability to choose champion model in production.
State of the art automated versioning system for deployed models in staging and production environments. The system considers data, model source code and pipelines.
Easy to use interface to aggregate any supported data science tool, data warehouse, cloud/on-prem/hybrid ecosystem and AI platform in a single unified workflow.
Ability to set permissions, define access-control and enable secret management. We also support activity tracking and collaboration across teams.
15 years of combined experience in business development, data engineering and devops.
Technology & Innovation