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Democratized AI
You can trust.
Innovation
you can scale.
Security
Ensure data privacy as well as compliance to industry regulatory standards that are critical for business use cases
Granular Access Controls
Role and attribute based access controls at the data element level ensures secure discovery and model building.
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Data Cell-Level Security
Responsible data handling through encryption for privacy and data snapshots for reliability.
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Policy Management
Identify, implement, and manage the rules and procedures required for accessing and deploying models.
Governance
Achieve transparency and accountability of AI projects with audit trails, model governance, and transparency.
AI Audit Trails
Monitor and track the ML lifecycle with AI workflows to mitigate drift and ensure model reliability.
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Model & Data Governance
Define and enforce practices and processes to help ensure the formal management of data assets.
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Transparency
Eliminate fear of bias with complete transparency of model results and how these results are achieved.
Ease of use
Democratization of data and the automation of the AI lifecycle empowers all data users to be innovators — accelerating the time-to-market of new AI solutions.
Low/No-Code AI Development
Abstract the complexities of AI through an intuitive and graphical user interface for data science and modeling.
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Data Fusion
Simplify data access, ingestion, and harmonization by fusing disparate sources in a centralized data reservoir.
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ML Ops Automation & Serving
Streamline the ML lifecycle by automating mundane ML Ops tasks to accelerate time-to-market of new AI solutions.
Explainability
Build trust of AI across the business and data teams, which will increase adoption of AI to enable more use cases and solutions.
Business Explainability
Build trust with the business through model performance insights to mitigate risk and ensure AI solutions are production ready.
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Visual AI Explainability
Ensure clear understanding of how your models work for both technical and business audiences.
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Model Simulation
Ensure resiliency and accuracy of models through exhaustive stress testing.
Collaboration
Dismantle cross-team silos between data teams and the business to boost trust and productivity across the organization.
Centralized Platform For All
A collaborative environment that enables all members of the data team to work together to fuel AI-powered innovations.
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Data Democratization
Remove data engineering barriers to enable open access, exploration, and analysis of data.
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Shared Projects
Increase collaboration and productivity with shared projects that facilitate asset sharing and reuse.
security
Governance
Ease of use
Expainability
Collaboration
Measurable success, immeasurable impact
GROWING REVENUE MARKET SHARE
HIGHER OPERATIONAL EFFICIENCY
LOWER OPERATION COSTS
FUTURE-PROOF YOUR BUSINESS
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