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Zeblok Computational delivers long-term value by helping our customers and partners build products powered by Artificial Intelligence.
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Platform Gap
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Application Gap
Enterprise AI development teams need comprehensive lifecycle management across multi-class, multi-model ecosystems.
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Integration Gap
Enterprise AI needs secure model serving, strict compliance, and deployment of AI models across different environments.
Simplicity and consistency across heterogenous environments are critical to developer success.
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Platform Gap
Limited choices force enterprises to move their data close to the AI stack of large hyperscalers for training and inference resulting in lock-in, data risk, wasted infrastructure and dev ops investments, and inability to access to discontinued GPUs.
Businesses need to move AI Stack to their data as opposed to other way around.
Application Gap
AI developers want plug n' play AI frameworks to rapidly build ML applications like AI-driven search, chatbots, AI-driven insights, descriptive analytics and predictive analytics.
Enterprise AI developer teams need comprehensive lifecycle management across multi-class, multi-modal, multi-cloud ecosystems.
Integration Gap
Integrating Ai inferences to applications and business processes requires ability to aggregate data, and to train and release multi-class Ai assets (vision, NLP, LLM, voice, traditional ML/DL) as Ai-APIs.
Enterprise Ai needs secure model serving, strict compliance, and deployment of AI models across different environments.
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Usability Gap
Enterprises want public cloud-like experiences across hybrid-cloud, on-premises, and cloud-to-edge. Easy to adopt, simple to use, scalable environments are needed to allocate resources, package inferences, and securely distribute software.
Simplicity and consistency across heterogenous environments are critical to developer success.
PRODUCTIVITY
Ai-MicroCloud® uniquely combines Ai-Model operations and Infrastructure-as-Code to create a comprehensive Ai software lifecycle management platform.
- Accelerate model development
- Reduce modeling costs
- Improve modeler productivity
- Streamline and automate using Infrastructure-as-Code
- Build better models, faster
With Zeblok, IT becomes low-touch and fully automated, enabling multi-disciplinary teams to collaborate and increase reuse, resulting in increased organizational productivity.
COMPOSABILITY
Ai-MicroCloud manages composable components and resources. With Plug n' Play ISV capabilities, the platform is extensible across any Ai use case and workload from Cloud Services Providers to Enterprise AI
- Composable components
- Plug n' Play ISVs
- Composable components
- Composable resources
- Static & dynamic allocation
PORTABILITY
Streamlined automation accelerates provisioning across hybrid, multi-cloud and bare metal in minutes instead of hours and days.
- Provision in less than 15 minutes across any hyperscaler
- Provision in less than 30 minutes on bare metal servers
- Zero cloud or infrastructure skills needed
- Cloud native portability across any public or private cloud
- Bring DL & ML DevSecOps platform to your data, instead of other way around.
SCALABILITY
Ai-MicroCloud® autoscales for HOC fine-tuning workloads saving critical resources for training experiment pipelines and Ai-inference workloads.
- Provision, manage and monitor 1000s of cloud-to-edge Ai locations
- Ai Deployment-as-a-Service
- Hybrid, hyperscaler, or on-premises
- Auto-scaling for HPC workloads
- Ai Tuning-as-a-Service
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LAUNCH
Zero touch infrastructure provisioning.
IMPORT
Third Party or Home Grown Docker applications / Notebooks.
AGGREGATE
Third Party or Open Source components as managed services.
JUMPSTART
Productive model HUB. Import Foundational Models.
PLAYGROUND
Rapidly load data, prototype and test in Jupiter notebooks.
COLLABORATE
Multiple roles. Snapshot work and share.
BUILD
Workstation, also known as Studio environment for model training.
ORCHESTRATE
Workloads on to CPUs/GPUs with vertical and horizontal scaling.
COMPOSE
Static and dynamic resource plans. CLI generates containers.
DEPLOY
Microservices, Workstations, APIs and Pipeline jobs.
DATA
Drag n' drop into object or block store abstractions for training.
AUTOMATE
Python power users use SDO and CLI to automate end-to-end pipelines.
- All
- Banking & Fintech
- Manufacturing
- Intelligent Infrastucture
Fraud Detection & Prevention
Quickly and accurately analyze large volumes of financial data. ML algorithms can learn from historical financial transactions, spotting patterns, making predictions.
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Insurance & Risk Assessment
Machine Learning algorithms enable more accurate and efficient risk assessments. Lowering human error, increasing speed, and analyzing vast amounts of data from multiple sources is transforming insurance.
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LLM and Generative Ai Powered Chatbots
LLM and Generative Ai powered chatbots provide 24/7 personalized support, financial advice, routine inquiry management, and in-depthanalysis frees up human resources to focus on complex requests.
Predictive Maintenance
AI can analyze equipment data to anticipate potential faults and optimize maintenance schedules, which can reduce downtime and increase operational efficiency. Scaling the use of powerful analytical engines, ML can lower infrastructure maintenance costs and risks.
Digital Twins in Manufacturing
Generative Ai enables creation of digital twins - virtual replicas of physical assets of processes. Using real-time data analysis from sensors, manufacturers create accurate digital representations of products, production, or whole factories.
Connected Factories
Connected factories incorporate Ai into production process to build intelligent, network ecosystems and smart factories. Ai-driven linked factories lower costs, increase efficiency, and right size production through adaptive manufacturing ecosystems adjusting to changing market demands.
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Autonomous Systems and Infrastructure
Autonomous Intelligent Infrastructure requires deployment of new ML-driven systems such as scalable edge networks, low-latency, secure wireless position-navigation systems, situational sensors (radars, Lidar, sonar, cameras), and edge ingestion through computer vision, NLP and other methods.
Zeblok-Ai Digital Foundations Blog
Digital Foundation for Intelligent Infrastructure Part I New Economy Brain
