About Ai-MicroCloud

Our mission is to aggregate AI assets, fine tune and deploy AI models from anywhere, across environments from cloud to edge. Ai-MicroCloud® provides a single, cohesive, turnkey, cloud native AI environment for development, training, and deployment of an end-to-end AI/ML solution to production from Cloud-to-Edge. It's a comprehensive Ai-Application Lifecycle Management technology that brings the Al stack to data instead of vice versa. It increases the portability, composability, and scalability of Enterprise Al solutions while increasing collaboration, productivity, and reuse of enterprise Al assets.

Some of the features include:

Aggregating diverse AI assets including various AI models (such as vision, language, time-series, and traditional models), custom microservices, headless workflow processing, batch processing, APIs, datasets, and more.
Few-click model serving & monitoring.
Comprehensive Ai-Application Lifecycle Management.
Integrated Generative Ai Suite.
Integrated Time-Series Suite.
Custom Enterprise Ai-AppStore.
Public Cloud Experience On-Premises.
No Vendor lock-in.

and much more.

Benefits in Brief

Collaboration: As-a-Service execution environment enables component sharing
No vendor Lock-in: No lock-in for Public Cloud, Private Cloud or any OEM manufacturer.
Easy Deployment: Consistent delivery of software assets across multi-cloud automation.
Future Proof: Cloud Native Architecture ingests multiclass Ai Models NLP, Vision, Voice.
Scalability: Infrastructure-as-Code scales to 1000s of Edge locations version control.
Aggregation & Reuse: Combine open-source models & in-house models with APIs.
Integration: Composability containers make enterprise CI/CD pipelines easier.
Performance: Post-training optimization of models for real-time use cases.

SDK

We provide a native Python Zeblok SDK to help integrate users' MLOps workflows with the Zeblok Ai-MicroCloud platform.

Blogs

Video Assets

ISVs

Zeblok's ISV onboarding program is designed to validate ISVs' AI algorithms for smooth functioning on the Zeblok Ai-MicroCloud®, installed within public cloud environments (AWS, Azure), and on certified MEC hardware SKU's to meet key operational criteria, including technology alignment (containerized solution), infrastructure topology alignment (cloud, Edge, hybrid-cloud, and on-prem), optimization alignment (leveraging Intel OpenVino™ and oneAPI™ toolkits).

NextNeed for Ai-MicroCloud

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Some of the features include:

Aggregating diverse AI assets including various AI models (such as vision, language, time-series, and traditional models), custom microservices, headless workflow processing, batch processing, APIs, datasets, and more.

Few-click model serving & monitoring.

Comprehensive Ai-Application Lifecycle Management.

Integrated Generative Ai Suite.

Integrated Time-Series Suite.

Custom Enterprise Ai-AppStore.

Public Cloud Experience On-Premises.

No Vendor lock-in.

and much more.

Benefits in Brief

Collaboration: As-a-Service execution environment enables component sharing

No vendor Lock-in: No lock-in for Public Cloud, Private Cloud or any OEM manufacturer.

Easy Deployment: Consistent delivery of software assets across multi-cloud automation.

Future Proof: Cloud Native Architecture ingests multiclass Ai Models NLP, Vision, Voice.

Scalability: Infrastructure-as-Code scales to 1000s of Edge locations version control.

Aggregation & Reuse: Combine open-source models & in-house models with APIs.

Integration: Composability containers make enterprise CI/CD pipelines easier.

Performance: Post-training optimization of models for real-time use cases.

ISVs