Agentic AI Training in Tashkent

Generative AI and Agentic AI represent two powerful paradigms propelling the next wave of automation and intelligence. One is dedicated to content creation, while the other focuses on goal-oriented, autonomous actions.

This instructor-led, live training (available online or on-site) is designed for intermediate-level AI and technical professionals who want to learn how to build, evaluate, and integrate generative and agentic AI into real-world applications.

By the end of this training, participants will be able to:

• Comprehend the architecture and capabilities of generative AI systems.
• Explore the emergence of autonomous AI agents and their extension of LLMs.
• Apply prompt engineering and tool integrations for practical deployments.
• Compare models, tools, and techniques for responsible deployment.

Format of the Course

• Interactive lecture and discussion.
• Hands-on use of generative and agentic AI tools in real-world scenarios.
• Guided exercises focused on content generation and autonomous workflows.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Agentic AI represents an emerging category of systems designed for autonomous decision-making, task execution, and workflow orchestration.

This instructor-led live training, available online or onsite, targets intermediate-level professionals seeking to comprehend how agentic AI will transform organizational workflows, talent strategies, and job design.

Upon completing the course, participants will be able to:

• Assess the capabilities and constraints of agentic AI within enterprise environments.
• Identify opportunities for automating, augmenting, and redesigning tasks.
• Evaluate workforce implications and formulate responsible adoption strategies.
• Plan governance frameworks to ensure safe, transparent, and compliant AI deployment.

Course Format

• Interactive lectures and discussions.
• Practical exercises and scenario-based analysis.
• Guided, hands-on exploration of agentic workflows.

Customization Options

• To request customized training for this course, please contact us to arrange details.

The Practical Agentic AI Bootcamp is an immersive, project-centric course aimed at providing participants with hands-on experience in designing, constructing, and deploying autonomous AI agents using Python. Through five increasingly complex projects, attendees will delve into agentic design patterns, prompt workflows, API orchestration, and practical integration scenarios.

This instructor-led live training (available online or onsite) targets intermediate-level professionals eager to transition quickly from theoretical concepts to implementation by creating functional prototypes of agentic AI applications.

Upon completion of this training, participants will be equipped to:

• Grasp agentic AI architectures and fundamental design principles.
• Create, test, and deploy several agent-based applications in Python.
• Seamlessly integrate agents with external tools, APIs, and databases.
• Refine prompts and workflows to enhance performance and reliability.
• Implement best practices for monitoring, versioning, and scaling agent systems.

Course Format

• Interactive lectures combined with guided coding sessions.
• Practical project development and debugging exercises.
• Live demonstration of full-cycle agent deployment.

Customization Options

• For information on customizing this training, please contact us to arrange a session.

Edge & Lightweight Agents is a practical course focused on deploying agentic AI workloads on resource-constrained devices. Participants learn to build, optimize, and manage lightweight agents capable of local reasoning and inference, improving speed, privacy, and reliability in distributed environments. The course emphasises performance tuning, low-latency design, and hardware–software integration.

This instructor-led, live training (online or on-site) is aimed at intermediate-level professionals who wish to implement and optimise on-device agentic systems using Python and edge AI frameworks.

By the end of this training, participants will be able to:

• Understand the architecture and challenges of running agentic AI on edge devices.
• Design lightweight agent loops suitable for constrained environments.
• Implement local inference using TensorFlow Lite, PyTorch Mobile, and ONNX.
• Integrate agents with sensors, actuators, and IoT platforms.
• Optimise performance, energy use, and latency for real-time operation.

Format of the Course

• Interactive lecture and practical demonstrations.
• Hands-on development in local or emulated environments.
• Project-based learning and guided implementation exercises.

Course Customisation Options

• To request a customised training for this course, please contact us to arrange.

Agentic AI refers to systems that act autonomously to achieve goals, integrating reasoning, memory, and tool use. This course provides a structured introduction to agentic AI concepts, focusing on prompt engineering, architectural design patterns, and responsible use practices. Participants will gain foundational knowledge for building, guiding, and deploying agents effectively and safely.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level professionals who wish to understand how to design, prompt, and manage responsible agentic systems using practical frameworks and examples.

By the end of this training, participants will be able to:

• Explain the core principles and lifecycle of agentic AI systems.
• Apply prompt engineering techniques for effective task completion.
• Design simple agent workflows using tool access and decision logic.
• Implement safety, governance, and responsible-use considerations in AI agents.
• Build a prototype agent using open frameworks and Python.

Format of the Course

• Interactive lecture and guided demonstration.
• Hands-on exercises and coding practice.
• Collaborative discussions and case-based activities.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Agentic AI for Business Automation is a practical course designed to equip participants with the skills to design, integrate, and scale AI-driven agents for real-world business processes. The course focuses on identifying automation opportunities, integrating tools, and developing practical use cases across customer service, supply chain, and marketing workflows.

This instructor-led, live training (available online or on-site) is tailored for intermediate-level professionals who wish to implement AI-powered automation using no-code, low-code, and Python-based approaches.

By the end of this training, participants will be able to:

• Identify key areas where agentic AI can enhance process efficiency and drive innovation.
• Map workflows suitable for AI agent integration.
• Implement automation using APIs and orchestration tools.
• Integrate AI models into real business scenarios with measurable impact.
• Develop governance and monitoring frameworks for AI-driven operations.

Course Format

• Interactive lectures and practical demonstrations.
• Hands-on exercises and guided projects.
• Live implementation within a sandbox automation environment.

Course Customization Options

• To request a customized training session for this course, please contact us to arrange.

This course delves into the design, coordination, and implementation of multi-agent systems (MAS) utilizing Python. Participants will acquire the skills to construct agents that communicate, collaborate, and adapt to achieve collective goals within complex and dynamic environments.

This instructor-led, live training (available online or onsite) is targeted at advanced-level professionals seeking to design and implement multi-agent systems for intelligent automation, simulation, and decision-making applications.

Upon completion of this training, participants will be able to:

• Grasp the architecture and fundamental principles of multi-agent systems.
• Develop agents capable of effective communication, coordination, and negotiation.
• Implement distributed environments for agent interactions.
• Apply reinforcement learning and planning techniques in multi-agent contexts.
• Simulate both cooperative and competitive agent behaviors.
• Design hybrid workflows that integrate humans and intelligent agents.

Course Format

• Instructor-led lectures and live demonstrations.
• Hands-on exercises utilizing open-source agent frameworks.
• A practical group project simulating a multi-agent scenario.

Course Customization Options

• To request customized training for this course, please contact us to arrange.

This course delves into the core principles and practical implementation of reinforcement learning (RL) and sequential decision-making within agentic AI systems. Learners will gain the skills to design, train, and evaluate agents that dynamically interact with their surroundings to achieve long-term objectives through continuous learning and adaptation.

Delivered as an instructor-led live training (available online or onsite), this program is tailored for advanced engineers and researchers looking to incorporate reinforcement learning and planning algorithms into agentic systems for applications in automation, robotics, and adaptive reasoning.

Upon completion of this training, participants will be able to:

• Grasp the mathematical underpinnings of reinforcement learning and decision-making.
• Apply key RL algorithms such as DQN, PPO, and A3C using Python and PyTorch.
• Construct environments with OpenAI Gym and develop custom simulation scenarios.
• Train, evaluate, and debug agents for both continuous and discrete control tasks.
• Deploy reinforcement learning techniques in agentic AI use cases, including robotics and planning.
• Effectively balance exploration, exploitation, and safety constraints for real-world deployment.

Format of the Course

• Instructor-led lectures accompanied by live coding demonstrations.
• Practical exercises utilizing open-source frameworks and simulation environments.
• A capstone project focused on integrating decision-making capabilities into an agentic AI system.

Course Customization Options

• For customized training arrangements, please reach out to us.

This course delves into scaling, operationalizing, and managing agentic AI systems within production environments, with a strong emphasis on reliability, observability, and cost efficiency.

Designed as an instructor-led, live training (available online or onsite), this program is tailored for advanced-level professionals seeking to develop resilient, observable, and cost-optimized pipelines for large-scale agentic systems.

By the end of this training, participants will gain the ability to:

• Architect scalable solutions for agentic AI workloads.
• Deploy observability and monitoring frameworks specifically designed for agent behavior and interactions.
• Utilize performance tuning and resource optimization techniques for long-running agent processes.
• Manage costs and prevent “agent sprawl” through strategic policy implementation, orchestration, and automation.
• Integrate MLOps best practices for continuous deployment, versioning, and rollback of agentic services.

Course Format

• Hands-on, engineering-focused sessions featuring live infrastructure examples.
• Interactive discussions on architectural trade-offs and observability challenges.
• Capstone exercise: deploy and monitor a cost-controlled, production-grade agentic system.

Customization Options

• To request a tailored training session, please contact us for arrangements.

WrenAI empowers organisations to move beyond static dashboards toward conversational analytics and embedded generative BI. This transition demands careful adoption planning, asset migration, and effective change management practices.

This instructor-led, live training (available online or on-site) is designed for intermediate-level BI and data platform professionals seeking to modernise legacy BI systems using WrenAI.

By the end of this training, participants will be able to:

• Evaluate legacy BI environments and identify modernisation opportunities.
• Plan and execute migrations from static dashboards to WrenAI.
• Adopt conversational analytics and embedded GenBI capabilities.
• Lead organisational change management for BI modernisation.

Course Format

• Interactive lectures and discussions.
• Hands-on exercises covering migration and adoption planning.
• Practical labs focused on conversational analytics and embedded GenBI.

Course Customisation Options

• To request a customised training session for this course, please contact us to arrange.

This course explores governance, identity management, and adversarial testing for agentic AI systems, emphasizing enterprise-safe deployment strategies and practical red-teaming methodologies.

This instructor-led, live training (available online or onsite) is designed for advanced practitioners aiming to design, secure, and evaluate agent-based AI systems within production environments.

Upon completion of this training, participants will be equipped to:

• Establish governance models and policies to ensure safe agentic AI deployments.
• Design non-human identity and authentication flows for agents, ensuring least-privilege access.
• Implement access controls, audit trails, and observability mechanisms specifically tailored for autonomous agents.
• Plan and execute red-team exercises to identify potential misuse, escalation paths, and data exfiltration risks.
• Mitigate common threats to agentic systems through policy adjustments, engineering controls, and monitoring.

Course Format

• Interactive lectures combined with threat-modeling workshops.
• Hands-on labs covering identity provisioning, policy enforcement, and adversary simulation.
• Red-team/blue-team exercises and a final course assessment.

Customization Options

• For customized training requests, please contact us to make arrangements.

Python is the core language powering the development and orchestration of autonomous AI agents. This course focuses on practical implementation using modern SDKs and frameworks such as LangChain and AutoGen to build, connect, and manage agent workflows.

This instructor-led, live training (online or onsite) is aimed at intermediate-level backend engineers, platform engineers, and ML engineers who wish to implement and orchestrate autonomous agents using Python tooling and APIs.

By the end of this training, participants will be able to:

• Set up and configure Python-based environments for agentic systems.
• Use popular agent SDKs like LangChain and AutoGen to create functional agents.
• Integrate tools and APIs to extend agent capabilities.
• Orchestrate multi-agent workflows and communication patterns.
• Apply best practices for debugging, testing, and maintaining agentic codebases.

Format of the Course

• Interactive lecture and discussion.
• Hands-on programming exercises and live demos.
• Practical projects building end-to-end agent workflows.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

WrenAI enables finance teams to model KPIs, integrate standardized metrics, and design dashboards that align with regulatory requirements and audit standards.

This instructor-led, live training (available online or on-site) is designed for intermediate to advanced-level finance professionals who wish to leverage WrenAI to build compliant financial data models and dashboards that support decision-making and risk management.

By the end of this training, participants will be able to:

• Model financial KPIs and metrics using WrenAI.
• Develop dashboards aligned with regulatory and audit requirements.
• Integrate WrenAI with finance data sources for real-time reporting.
• Apply best practices in financial analytics and risk monitoring.

Course Format

• Interactive lectures and discussions.
• Hands-on exercises using financial data models.
• Practical labs focused on dashboard design and compliance reporting.

Course Customization Options

• To request a customized version of this training, please contact us to arrange.

This course imparts practical engineering skills for designing, building, testing, and deploying agentic (autonomous) systems using Python. Key topics include the agent loop, tool integrations, memory and state management, orchestration patterns, safety controls, and production-ready considerations.

This instructor-led live training is available online or on-site. It is designed for intermediate to advanced ML engineers, AI developers, and software engineers looking to construct robust, production-ready autonomous agents with Python.

Upon completing this training, participants will be capable of:

• Designing and implementing the agent loop and decision-making workflows.
• Integrating external tools and APIs to expand agent capabilities.
• Implementing short-term and long-term memory architectures for agents.
• Coordinating multi-step orchestrations and ensuring agent composability.
• Applying best practices for safety, access control, and observability in deployed agents.

Course Format

• Interactive lectures and discussions.
• Hands-on labs for building agents using Python and popular SDKs.
• Project-based exercises resulting in deployable prototypes.

Course Customization Options

• For customized training requests, please contact us to make arrangements.

WrenAI transforms natural language into SQL and powers AI-driven analytics, making data access more intuitive and rapid. For enterprise deployments, rigorous quality assurance and observability standards are vital to guarantee accuracy, reliability, and regulatory compliance.

This live, instructor-led training (available online or onsite) is designed for advanced data and analytics professionals who aim to assess query precision, optimize prompts, and establish observability protocols for monitoring WrenAI in production environments.

Upon completing this training, participants will be equipped to:

• Assess the precision and dependability of Natural Language to SQL outputs.
• Implement prompt tuning strategies to enhance system performance.
• Track performance drift and query patterns over time.
• Equip WrenAI with logging and observability frameworks.

Course Structure

• Engaging lectures and interactive discussions.
• Practical exercises focused on evaluation and tuning techniques.
• Hands-on labs covering observability and monitoring integrations.

Customization Options

• To arrange a tailored training session for this course, please reach out to us.

Agentic AI is an approach where AI systems plan, reason, and take tool-using actions to accomplish goals within defined constraints.

This instructor-led, live training (online or onsite) is aimed at intermediate-level healthcare and data teams who wish to design, evaluate, and govern agentic AI solutions for clinical and operational use cases.

By the end of this training, participants will be able to:

• Explain agentic AI concepts and constraints within healthcare contexts.
• Design safe agent workflows incorporating planning, memory, and tool usage.
• Build retrieval-augmented agents over clinical documents and knowledge bases.
• Evaluate, monitor, and govern agent behaviour using guardrails and human-in-the-loop controls.

Format of the Course

• Interactive lecture and facilitated discussion.
• Guided labs and code walkthroughs in a sandbox environment.
• Scenario-based exercises focusing on safety, evaluation, and governance.

Course Customisation Options

• To request a customised training for this course, please contact us to arrange.

WrenAI is an AI-powered analytics platform designed to connect data, model insights, and generate dashboards. In enterprise environments, robust governance and security are critical to ensuring safe and compliant adoption.

This instructor-led, live training (available online or on-site) is tailored for advanced-level enterprise professionals who aim to implement governance, compliance, and security patterns for WrenAI at scale.

By the end of this training, participants will be able to:

• Design and implement permissioning models within WrenAI.
• Apply auditability and monitoring practices to meet compliance requirements.
• Configure secure environments with enterprise-grade controls.
• Safely deploy WrenAI across large-scale organisations.

Course Format

• Interactive lectures and group discussions.
• Hands-on labs focused on governance and security configurations.
• Practical exercises simulating real-world enterprise deployment scenarios.

Course Customisation Options

• To request a customised version of this course, please contact us to make arrangements.

This instructor-led, live training in Tashkent (online or on-site) is designed for intermediate-level AI developers and automation specialists who wish to integrate agentic capabilities into AI-powered applications.

By the end of this training, participants will be able to:

• Understand the principles of agentic AI and autonomous decision-making.
• Implement goal-driven AI agents using self-optimisation techniques.
• Integrate multi-agent collaboration to solve complex problems.
• Enhance AI-human interaction through adaptive user experiences.
• Deploy agentic AI models in real-world applications.

WrenAI Spreadsheets and Metrics Library enable fast reporting through AI-powered spreadsheet workflows and a library of pre-built, cross-platform business metrics.

This instructor-led, live training (available online or on-site) is designed for beginner to intermediate-level operations professionals who aim to accelerate reporting and analysis using WrenAI Spreadsheets and the Metrics Library.

By the end of this training, participants will be able to:

• Build AI-powered spreadsheets for data analysis and reporting.
• Leverage the WrenAI Metrics Library for standardized KPIs.
• Connect spreadsheets to multiple data sources for live updates.
• Create automated workflows to streamline operational reporting.

Course Format

• Interactive lectures and group discussions.
• Hands-on spreadsheet building using WrenAI.
• Practical exercises focused on metrics and KPI reporting.

Customization Options

• To request a customized training session for this course, please contact us to arrange.

This instructor-led, live training in Tashkent (online or onsite) is designed for advanced-level professionals seeking to develop and optimize multi-agent systems using Agentic AI frameworks.

By the end of this training, participants will be able to:

• Grasp the core principles of Agentic AI within multi-agent environments.
• Build AI-driven agents capable of autonomous interaction.
• Implement reinforcement learning techniques to foster adaptive AI behavior.
• Enhance collaboration and manage competition among multiple agents.
• Apply Agentic AI solutions in robotics, gaming, and enterprise automation.

The WrenAI API serves as a robust interface designed to convert natural language into SQL queries, facilitate the creation of custom applications, and embed visual charts within internal platforms.

This instructor-led training, available both online and on-site, is designed for intermediate-level engineers looking to leverage the WrenAI API for practical use cases, such as generating SQL, visualizing data, and integrating applications.

Upon completion of this training, participants will be capable of:

• Authenticating and linking applications to the WrenAI API.
• Generating SQL queries from natural language inputs.
• Creating and embedding charts via API endpoints.
• Integrating WrenAI into backend systems and internal tools.

Course Format

• Interactive lectures and discussions.
• Practical exercises involving API calls and integrations.
• Real-world projects that connect applications, charts, and data pipelines.

Customization Options

• For inquiries regarding customized training for this course, please contact us to arrange details.

This instructor-led, live training in Tashkent (available online or on-site) is designed for advanced-level professionals aiming to leverage Agentic AI for enterprise-scale automation and strategic AI adoption.

Upon completion of this training, participants will be able to:

• Understand the role of Agentic AI in enterprise applications.
• Integrate autonomous AI agents with enterprise systems.
• Optimize AI-driven workflows for scalability and efficiency.
• Ensure compliance, security, and governance in AI automation.
• Develop AI-driven business strategies for digital transformation.

WrenAI Cloud is a contemporary platform designed for linking data sources, structuring data, and constructing interactive dashboards.

This instructor-led, live training session, available either online or onsite, targets beginner to intermediate data professionals eager to master setting up WrenAI Cloud, modeling data, and visualizing insights through dashboards.

Upon completing this training, participants will be capable of:

• Setting up and configuring WrenAI Cloud environments.
• Linking WrenAI Cloud to various data sources.
• Modeling data and defining relationships for analytics.
• Creating interactive dashboards to derive business insights.

Format of the Course

• Interactive lectures and discussions.
• Practical cloud platform configuration and data modeling.
• Hands-on exercises in dashboard creation and visualization.

Course Customization Options

• For a customized training version of this course, please contact us to arrange.

This instructor-led, live training in Tashkent (online or onsite) is aimed at advanced-level professionals who wish to leverage Agentic AI for decision-making in complex business and technical scenarios.

By the end of this training, participants will be able to:

• Understand the principles of autonomous decision-making in AI.
• Design and implement AI agents that operate with minimal human intervention.
• Integrate Agentic AI into automation workflows and business systems.
• Optimize AI-driven decision processes for efficiency and scalability.
• Ensure compliance, security, and ethical considerations in AI autonomy.

WrenAI is an open-source generative BI tool that facilitates natural language to SQL conversion and semantic data modeling.

This instructor-led, live training (available online or onsite) is designed for advanced data engineers, analytics engineers, and ML engineers aiming to build robust semantic layers, tune prompts, and ensure reliable SQL generation.

Upon completing this training, participants will be able to:

• Implement semantic models to establish consistent metric definitions across teams.
• Optimize text-to-SQL performance for enhanced accuracy and scalability.
• Configure and enforce guardrails to prevent invalid or risky queries.
• Integrate WrenAI OSS into data pipelines and analytics workflows.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practical sessions.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This live, instructor-led training in Tashkent (available online or on-site) is tailored for AI engineers, machine learning researchers, and developers at an intermediate level who seek to build and deploy Agentic AI systems in real-world contexts.

Upon completing this training, participants will be equipped to:

• Grasp the fundamental concepts underlying Agentic AI systems.
• Deploy AI agents capable of autonomous reasoning and executing actions.
• Connect Agentic AI with APIs and external services.
• Enhance multi-agent interactions to handle complex tasks efficiently.
• Tackle ethical, security, and scalability issues inherent in Agentic AI.

WrenAI empowers SaaS providers to seamlessly integrate generative business intelligence (GenBI) directly into their customer-facing applications. This course provides SaaS teams with the essential skills to connect Wren AI via its Embedded API, configure white-label analytics, and manage multi-tenant deployments effectively.

This instructor-led, live training (available online or onsite) is designed for intermediate to advanced SaaS product leaders, data engineers, and full-stack developers aiming to deploy WrenAI as an embedded analytics solution within SaaS environments.

Upon completion of this training, participants will be capable of:

• Integrating WrenAI via the Embedded API for customer-facing applications.
• Implementing white-label conversational BI with tailored branding and customization.
• Designing secure and scalable multi-tenant deployments.
• Monitoring usage, optimizing performance, and ensuring compliance in SaaS environments.

Course Format

• Interactive lectures and discussions.
• Hands-on labs utilizing the WrenAI Embedded API.
• Workshop: Design and deploy a white-label analytics feature for a specific SaaS use case.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in Tashkent (online or onsite) is aimed at beginner-level professionals who wish to understand the fundamental principles of Agentic AI, its capabilities, and its potential impact on industries.

By the end of this training, participants will be able to:

• Understand the core principles of Agentic AI.
• Differentiate between traditional AI and autonomous AI agents.
• Explore real-world applications of Agentic AI in various industries.
• Assess the benefits and challenges of deploying autonomous AI systems.
• Analyze the ethical and security considerations of Agentic AI.

WrenAI is a conversational analytics platform that translates natural-language queries into reliable analytics, enabling non-technical teams to generate insights quickly and consistently.

This instructor-led, live training (online or onsite) is aimed at intermediate-level product managers, analysts, and data champions who wish to adopt conversational analytics and build self-service BI capabilities with WrenAI.

By the end of this training, participants will be able to:

• Design conversational analytics workflows that surface reliable product insights.
• Create and maintain a standardized metrics layer for consistent reporting.
• Use natural-language to SQL features effectively to answer product questions.
• Embed WrenAI-driven self-service dashboards and guardrails in product workflows.

Format of the Course

• Interactive lecture and discussion.
• Hands-on labs with Wren AI and sample datasets.
• Workshop: build a self-service dashboard and conversational query set.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

AI agents are transitioning from experimental prototypes to autonomous production systems capable of operating across text, image, speech, and tool-driven workflows. This shift demands higher standards for engineering precision, resilience against adversarial attacks, and regulatory compliance. This instructor-led program guides advanced practitioners through the entire agent lifecycle, covering the design of single and multi-agent systems, the integration of multi-modal perception, and the orchestration of coordinated behaviors using modern frameworks. Through progressive Python-based hands-on labs, participants construct a production-ready multi-agent system, which they then rigorously stress-test using adversarial techniques and the Adversarial Robustness Toolbox. The curriculum concludes with alignment to NIST AI RMF, ISO/IEC 42001, the EU AI Act, and GDPR, alongside best practices for secure deployment, monitoring, and incident response, ensuring participants can deliver agents that are robust, defensible, and compliant.

This instructor-led live training in Tashkent (online or onsite) is designed for beginner to intermediate developers and cloud practitioners who wish to utilize Alibaba Cloud to build AI agents that can automate tasks, answer queries, and integrate with business systems.

By the end of this training, participants will understand AI agent architecture on Alibaba Cloud, construct a simple agent workflow, link an agent to enterprise knowledge and tools, and deploy and monitor the agent in a cloud environment.