From Adhoc to Scalable. Fragmented to Collaborative.
A unifying platform for organizations to accelerate value creation from data.
A unifying platform for organizations to accelerate value creation from data.
A unified platform binding people, artifacts and processes to build effective remote data science teams. Built with an underlying architecture which promotes creation, sharing and collaboration of reusable assets in an organization
Capitalize on work of existing projects
Discover re-usable artifacts & re-purpose them
Improved Governance
A no-code, drag and drop building environment to author rapid development of ML pipelines and streaming workflows - democratizing the creation of AI applications
Unlock potential of self-serving users
Scale AI-driven enterprise with more creators
More creative interation & faster time to market
Physarum platform comes with 200+ native AI algorithms, streaming tasks and data science functions which can be used across multiple projects. Physarum also provides an SDK for developers to add custom components - which can then be used by non-coding team-mates through GUI - sharing costs & time incurred from initial AI projects across other teams & related projects
200+ native AI algorithms streaming tasks and data science functions
SDK for developers
Sharing costs & ime incurred from initial AI projects
Create once, deploy in any cloud. A systematic and repeatable workflow for serverless deployment. Access deployment capabilities of Physarum engine through web interface, Physarum DSL or directly from Jupyter Notebooks
Accelerate deployment of ML features in production
Reduce infra cost with serverless deployment
Production grade reliablity
No kubernetes knowledge required
Wire together streaming components using a drag-and-drop builder. Physarum platforms automates the rest - deployment, scaling and lifecycle management of streaming applications
Infuse real-time with intelligence
Power ML driven custom experiences
Power automated decision making at scale
Automated deployment & scaling - with in built end-to-end observability
Create an organization-wide repository of ML features by centralizing the feature engineering effort with FeatureStore - leading to improved discoverability and re-usability of ML features across teams and projects
Democratization of Data Access
Improved reusability
ML PIPELINE
Automate creation of advanced ML models for Computer Vision, NLP and tabular data by identifying top performing ML pipelines. The pipeline can also be expressed through both workflow builder and DSL by chaining re-usable components
Automate creation of advanced ML models
Pipelines expressable through workflow builder and DSL
Supports all areas of ML, AI ie. Computer Vision, NL and tabular data
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STREAMING PIPELINE
Simplify streaming data pipelines using Physarum Streams - framework for development , deployment and monitoring of reactive streaming pipelines. A unified view for combining a dozens of integrations enabling data prep for ML
Simplify streaming data pipelines
Development , deployment and monitoring of reactive streaming pipelines
A unified view for combining a dozens of integrations
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Physarum is a platform where you can uncover all the possibilities of AI. It provide your team a collaborative workspace to work.
This use case is used for solving some problems in data science.
This use case is used for solving some problems in data science.
This use case is used for solving some problems in data science.
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