Shakudo provides an operating layer that integrates best-of-breed data and AI tools on a customer's cloud infrastructure, enabling automated DevOps and resource management. This approach enhances data stack reliability and performance while significantly reducing operational costs and maintenance burdens.
Funding
$10.8M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
GVFounders
Product
Problem
Organizations struggle to integrate and manage disparate data and AI tools across their cloud infrastructure, leading to increased operational costs, maintenance burdens, and security vulnerabilities. The complexity of managing diverse data stacks hinders agility and slows down the delivery of business value from data initiatives.
Solution
Shakudo offers an operating layer that integrates best-of-breed data and AI tools on a customer's cloud infrastructure, providing automated DevOps and resource management. This platform creates compatibility across various data tools, enhancing data stack reliability, performance, and cost-effectiveness. Shakudo allows users to build customized stacks tailored to their specific needs, manage collaboration and access through a unified interface, and optimize cloud costs with automated compute and scaling. By standardizing data stack environments and automating enforcement, Shakudo enables organizations to focus on leveraging data for business outcomes rather than managing infrastructure complexities.
Target Audience
Shakudo targets data science teams, AI/ML engineers, and data platform owners within medium to large enterprises seeking to streamline their data and AI infrastructure management.
Features
- Unified UI with automated DevOps for managing data stack collaboration, access, and costs
- Cloud compute management and autoscaling for optimized resource utilization
- Support for over 174 data stack components and thousands of connectors
- Standardized data stack environments with automated enforcement of organizational policies
- Role-Based Access Control (RBAC) with deep linking into stack components
- Container image vulnerability scanning and PyPI/CRAN package vulnerability scanning
- Support for on-prem and private cloud deployments
- Platform-wide audit trails and data lineage spanning the entire stack