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Scaling Artificial Intelligence (AI)

AI at scale requires a Data Collaboration Platform... or it will fail !

The era of AI being a distant, conceptual wish in the enterprise has long passed. Nowadays, organizations are eager to transition from merely experimenting with AI and ML projects to implementing it on a grand scale. However, the questions on how to take AI to market for the majority of businesses still vastly outweigh the answers.

Today's organizations are encountering three primary hurdles when it comes to scaling AI: 

1

Lack of confidence in operationalizing AI

A well-orchestrated AI strategy relies on a foundation of trustworthy data, coupled with automated tools that yield transparent and comprehensible results.

2

Difficulties in effectively managing data

The creation of responsible AI demands meticulous planning, as well as the reduction in the amount of data integration needed to access and use the data.

3

Adhering to the evolving landscape of AI regulations.

AI regulations should be implemented via a diverse set of stakeholders rather than a centralized body. Data Product ownership as a data model for AI allows streamlined compliance standards and efforts.

Cinchy's Data Collaboration Platform is ideally equipped to empower your organization to expand and expedite the roll out of AI in the organization, all while maintaining data quality and trustworthiness throughout your entire enterprise.

Data Collaboration is the key to unlock the true power of AI

Cinchy helps unlock AI potential in the enterprise by providing a comprehensive data management platform that addresses data integration challenges, promotes collaboration, ensures data security and governance, and streamlines AI development and deployment processes. 

1

Data Unification

Cinchy's platform offers a unified data model that connects and consolidates data from various sources across the organization. This unified view simplifies data access, ensuring that AI models have access to high-quality, consistent data.
Data Unification
2

Data Collaboration

It enables cross-functional teams to collaborate on data projects easily. This collaborative environment fosters better data governance, which is essential for scaling AI projects.
Data Collaboration
3

Data Security and Privacy

Cinchy places a strong emphasis on data security and privacy. This is crucial for handling sensitive data, ensuring compliance with regulations, and maintaining trust in AI applications.
Data Security and Privacy
4

Data Governance

It provides robust data governance capabilities, allowing organizations to define data policies, access controls, and data lineage. This governance framework is essential for maintaining data quality and ensuring compliance.
Data Governance
5

Scalability

Cinchy's architecture is designed for scalability. As AI initiatives grow, the platform can adapt to handle increased data volumes and the complexity of AI models.
Scalability
6

Integration

Cinchy can integrate with various AI tools and platforms, making it easier to incorporate AI capabilities into the existing enterprise ecosystem.
Integration
7

Rapid Development

It accelerates AI development by simplifying data integration and reducing the time spent on data preparation. This allows data scientists and analysts to focus on building and deploying AI models more quickly.
Rapid Development
8

Reduced Silos

By breaking down data silos and promoting data sharing and collaboration, Cinchy helps organizations leverage their data assets more effectively for AI initiatives.
Reduced Silos
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Connected data without the effort, time, and cost of traditional data integration.