Sovereign AI for Regulated Organizations: Controlling Data, Models and Inference Environments Training Course
Sovereign AI for Regulated Organizations: Controlling Data, Models and Inference Environments is a hands-on course that equips regulated organisations with the strategies to maintain strict control over their AI data, models, and runtime environments.
This instructor-led live training (available online or onsite) targets intermediate IT leaders, compliance officers, security teams, and enterprise architects seeking to leverage sovereign AI principles and governance frameworks. The goal is to design AI environments that safeguard sensitive data, meet localisation mandates, and minimise dependency on external vendors.
Upon completion of this training, participants will be able to:
- Articulate the fundamental principles of sovereign AI within a regulated organisation.
- Evaluate risks associated with data, models, and inference, particularly concerning hosting, logging, and third-party AI services.
- Establish governance controls for prompts, logs, access permissions, auditability, and localisation requirements.
- Develop a practical roadmap to reduce reliance on AI vendors while ensuring ongoing compliance.
Course Format
- Interactive lectures and discussions.
- Guided exercises and collaborative analysis sessions.
- Scenario-based planning activities focused on policy formulation and architectural decisions.
Course Customization Options
- To request tailored training for this course, please contact us to arrange accordingly.
Course Outline
Foundations of Sovereign AI
- Understanding what sovereign AI entails for regulated organisations
- Business, legal, and operational drivers
- Key control areas: data, models, infrastructure, and operations
Regulatory Requirements and Risk Mapping
- Data residency, privacy regulations, and sector-specific obligations
- Mapping sensitive data to specific AI use cases
- Identifying risks related to cross-border data transfer, logging practices, and third-party exposure
Governing Data, Prompts, and Logs
- Prompt governance and defining acceptable use boundaries
- Establishing logging policies for prompts, responses, and metadata
- Implementing retention, redaction, masking, and access control practices
- Exercise: reviewing an AI data flow to identify governance gaps
Model Hosting and Inference Environment Options
- Evaluating deployment choices: public API, private cloud, on-premise, and hybrid environments
- Key factors for determining where models should operate
- Balancing trade-offs among control, security, cost, and operational ownership
Vendor Dependence and Portability
- Recognising common lock-in patterns in models, tools, and platforms
- Achieving portability through modular architecture, open interfaces, and clear contractual terms
- Exercise: evaluating a vendor against sovereignty criteria
Governance Model and Action Planning
- Defining roles and responsibilities across IT, security, legal, and compliance teams
- Establishing approval workflows for use cases, models, and operational changes
- Meeting expectations for auditability, monitoring, and incident response
- Developing a practical sovereign AI roadmap and outlining next steps
Requirements
- A foundational understanding of AI concepts, data governance, and compliance requirements
- Familiarity with enterprise technology, cloud infrastructure, security protocols, or risk management decision-making
- No prior programming experience is required
Audience
- IT leaders, enterprise architects, and platform managers
- Risk, compliance, legal, and data governance professionals
- Security teams and business executives responsible for driving AI adoption in regulated sectors
Open Training Courses require 5+ participants.
Sovereign AI for Regulated Organizations: Controlling Data, Models and Inference Environments Training Course - Booking
Sovereign AI for Regulated Organizations: Controlling Data, Models and Inference Environments Training Course - Enquiry
Sovereign AI for Regulated Organizations: Controlling Data, Models and Inference Environments - Consultancy Enquiry
Upcoming Courses
Related Courses
Advanced LangGraph: Optimization, Debugging, and Monitoring Complex Graphs
35 HoursLangGraph serves as a framework for developing stateful, multi-agent LLM applications through composable graphs that maintain persistent state and allow precise control over execution flow.
This instructor-led live training, available both online and onsite, is tailored for advanced-level AI platform engineers, AI DevOps specialists, and ML architects aiming to optimize, debug, monitor, and manage production-grade LangGraph systems.
Upon completing this training, participants will be capable of:
- Designing and optimizing complex LangGraph topologies to enhance speed, reduce costs, and improve scalability.
- Building reliability through retries, timeouts, idempotency, and checkpoint-based recovery mechanisms.
- Debugging and tracing graph executions, inspecting states, and systematically reproducing production issues.
- Instrumenting graphs with logs, metrics, and traces; deploying to production; and monitoring SLAs and costs.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practice sessions.
- Hands-on implementation within a live-lab environment.
Customization Options
- To request customized training for this course, please contact us to arrange.
Building Coding Agents with Devstral: From Agent Design to Tooling
14 HoursDevstral is an open-source framework engineered for the creation and execution of coding agents capable of interacting with codebases, developer tools, and APIs to boost engineering productivity.
This instructor-led, live training, available online or onsite, targets intermediate to advanced-level ML engineers, developer-tooling teams, and SREs keen on designing, implementing, and optimizing coding agents using Devstral.
Upon completion of this training, participants will be equipped to:
- Set up and configure Devstral for coding agent development.
- Design agentic workflows for codebase exploration and modification.
- Integrate coding agents with developer tools and APIs.
- Implement best practices for secure and efficient agent deployment.
Course Format
- Interactive lecture and discussion.
- Ample exercises and practice opportunities.
- Hands-on implementation within a live-lab environment.
Customization Options
- To request customized training for this course, please contact us to arrange.
Open-Source Model Ops: Self-Hosting, Fine-Tuning and Governance with Devstral & Mistral Models
14 HoursDevstral and Mistral are open-source AI technologies engineered for flexible deployment, fine-tuning capabilities, and scalable integration.
This instructor-led live training, available both online and onsite, targets intermediate to advanced machine learning engineers, platform teams, and research engineers who aim to self-host, fine-tune, and govern Mistral and Devstral models within production environments.
Upon completing this training, participants will be able to:
- Establish and configure self-hosted environments for Mistral and Devstral models.
- Apply fine-tuning techniques to enhance performance for specific domains.
- Implement versioning, monitoring, and lifecycle governance protocols.
- Ensure security, regulatory compliance, and responsible usage of open-source models.
Course Format
- Interactive lectures and discussions.
- Practical exercises focused on self-hosting and fine-tuning.
- Live laboratory sessions for implementing governance and monitoring pipelines.
Customization Options
- To arrange a customized version of this course, please get in touch with us.
LangGraph Applications in Finance
35 HoursLangGraph serves as a framework designed for constructing stateful, multi-actor LLM applications through composable graphs that maintain persistent state and offer precise control over execution.
This instructor-led live training, available either online or on-site, targets intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based financial solutions with robust governance, observability, and compliance measures.
Upon completion of this training, participants will be equipped to:
- Design finance-specific LangGraph workflows that align with regulatory and audit requirements.
- Integrate financial data standards and ontologies into graph state and tooling.
- Implement reliability, safety, and human-in-the-loop controls for critical processes.
- Deploy, monitor, and optimize LangGraph systems to meet performance, cost, and SLA objectives.
Format of the Course
- Interactive lecture and discussion.
- Extensive exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
LangGraph Foundations: Graph-Based LLM Prompting and Chaining
14 HoursLangGraph is a framework designed for constructing graph-structured LLM applications that support planning, branching, tool use, memory, and controllable execution.
This instructor-led, live training (available online or onsite) is tailored for beginner-level developers, prompt engineers, and data practitioners who wish to design and build reliable, multi-step LLM workflows using LangGraph.
By the end of this training, participants will be able to:
- Explain core LangGraph concepts (nodes, edges, state) and when to use them.
- Build prompt chains that branch, call tools, and maintain memory.
- Integrate retrieval and external APIs into graph workflows.
- Test, debug, and evaluate LangGraph apps for reliability and safety.
Format of the Course
- Interactive lecture and facilitated discussion.
- Guided labs and code walkthroughs in a sandbox environment.
- Scenario-based exercises on design, testing, and evaluation.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
LangGraph in Healthcare: Workflow Orchestration for Regulated Environments
35 HoursLangGraph empowers stateful, multi-actor workflows driven by Large Language Models (LLMs), offering precise control over execution paths and state persistence. In the healthcare sector, these capabilities are essential for ensuring compliance, interoperability, and the development of decision-support systems that seamlessly align with medical workflows.
This instructor-led live training session is available both online and onsite. It is designed for intermediate to advanced-level professionals aiming to design, implement, and manage LangGraph-based healthcare solutions while effectively addressing regulatory, ethical, and operational challenges.
Upon completion of this training, participants will be able to:
- Design healthcare-specific LangGraph workflows that prioritize compliance and auditability.
- Integrate LangGraph applications with medical ontologies and standards such as FHIR, SNOMED CT, and ICD.
- Apply best practices for reliability, traceability, and explainability in sensitive environments.
- Deploy, monitor, and validate LangGraph applications within healthcare production settings.
Format of the Course
- Interactive lecture and discussion.
- Hands-on exercises with real-world case studies.
- Implementation practice in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
LangGraph for Legal Applications
35 HoursLangGraph serves as a framework designed for constructing stateful, multi-actor LLM applications through composable graphs that maintain persistent state and offer precise execution control.
This instructor-led, live training (available online or onsite) targets intermediate to advanced professionals seeking to design, implement, and operate LangGraph-based legal solutions equipped with necessary compliance, traceability, and governance controls.
Upon completion of this training, participants will be able to:
- Design legal-specific LangGraph workflows that ensure auditability and compliance.
- Integrate legal ontologies and document standards into graph state and processing workflows.
- Implement guardrails, human-in-the-loop approvals, and traceable decision paths.
- Deploy, monitor, and maintain LangGraph services in production environments with robust observability and cost controls.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practice sessions.
- Hands-on implementation in a live laboratory environment.
Customization Options
- To request customized training for this course, please contact us to arrange it.
Building Dynamic Workflows with LangGraph and LLM Agents
14 HoursLangGraph is a framework designed for composing graph-structured LLM workflows that support branching, tool use, memory, and controllable execution.
This instructor-led, live training (available online or onsite) is aimed at intermediate-level engineers and product teams who wish to combine LangGraph’s graph logic with LLM agent loops to build dynamic, context-aware applications such as customer support agents, decision trees, and information retrieval systems.
By the end of this training, participants will be able to:
- Design graph-based workflows that coordinate LLM agents, tools, and memory.
- Implement conditional routing, retries, and fallbacks for robust execution.
- Integrate retrieval, APIs, and structured outputs into agent loops.
- Evaluate, monitor, and harden agent behavior for reliability and safety.
Format of the Course
- Interactive lecture and facilitated discussion.
- Guided labs and code walkthroughs in a sandbox environment.
- Scenario-based design exercises and peer reviews.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
LangGraph for Marketing Automation
14 HoursLangGraph is a graph-based orchestration framework designed to enable conditional, multi-step workflows involving LLMs and tools, making it ideal for automating and personalizing content pipelines.
This instructor-led live training, available online or onsite, targets intermediate-level marketers, content strategists, and automation developers seeking to implement dynamic, branching email campaigns and content generation pipelines using LangGraph.
Upon completion of this training, participants will be able to:
- Design graph-structured content and email workflows incorporating conditional logic.
- Integrate LLMs, APIs, and data sources to facilitate automated personalization.
- Manage state, memory, and context throughout multi-step campaigns.
- Evaluate, monitor, and optimize workflow performance and delivery outcomes.
Course Format
- Interactive lectures and group discussions.
- Hands-on labs focused on implementing email workflows and content pipelines.
- Scenario-based exercises covering personalization, segmentation, and branching logic.
Course Customization Options
- To request customized training for this course, please contact us to arrange a session.
Le Chat Enterprise: Private ChatOps, Integrations & Admin Controls
14 HoursLe Chat Enterprise offers a private ChatOps solution, delivering secure, customizable, and governed conversational AI capabilities for organizations. It supports Role-Based Access Control (RBAC), Single Sign-On (SSO), connectors, and integrations with enterprise applications.
This instructor-led live training, available online or onsite, is designed for intermediate-level product managers, IT leaders, solution engineers, and security and compliance teams who aim to deploy, configure, and govern Le Chat Enterprise within enterprise environments.
Upon completion of this training, participants will be able to:
- Set up and configure Le Chat Enterprise for secure deployments.
- Enable RBAC, SSO, and compliance-driven controls.
- Integrate Le Chat with enterprise applications and data repositories.
- Design and implement governance and administrative playbooks for ChatOps.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practical sessions.
- Hands-on implementation in a live laboratory environment.
Course Customization Options
- To request a customized training session for this course, please contact us to arrange.
Cost-Effective LLM Architectures: Mistral at Scale (Performance / Cost Engineering)
14 HoursMistral is a high-performance family of large language models optimized for cost-effective production deployment at scale.
This instructor-led, live training (online or onsite) is aimed at advanced-level infrastructure engineers, cloud architects, and MLOps leads who wish to design, deploy, and optimize Mistral-based architectures for maximum throughput and minimum cost.
By the end of this training, participants will be able to:
- Implement scalable deployment patterns for Mistral Medium 3.
- Apply batching, quantization, and efficient serving strategies.
- Optimize inference costs while maintaining performance.
- Design production-ready serving topologies for enterprise workloads.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Productizing Conversational Assistants with Mistral Connectors & Integrations
14 HoursMistral AI serves as an open-source AI platform that empowers teams to construct and embed conversational assistants into both enterprise operations and customer-facing workflows.
This instructor-led live training, available either online or onsite, targets beginner to intermediate product managers, full-stack developers, and integration engineers looking to design, integrate, and productize conversational assistants using Mistral connectors and integrations.
Upon completion of this training, participants will be capable of:
- Integrating Mistral conversational models with enterprise and SaaS connectors.
- Implementing retrieval-augmented generation (RAG) to deliver grounded responses.
- Designing UX patterns for both internal and external chat assistants.
- Deploying assistants into product workflows for real-world applications.
Format of the Course
- Interactive lecture and discussion.
- Hands-on integration exercises.
- Live-lab development of conversational assistants.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Enterprise-Grade Deployments with Mistral Medium 3
14 HoursMistral Medium 3 is a high-performance, multimodal large language model engineered for robust deployment within enterprise settings.
This instructor-led live training, available either online or at your location, targets intermediate to advanced AI/ML engineers, platform architects, and MLOps professionals seeking to deploy, optimize, and secure Mistral Medium 3 for business-critical applications.
Upon completion of this training, participants will be equipped to:
- Deploy Mistral Medium 3 via API or self-hosted configurations.
- Enhance inference performance while managing costs effectively.
- Develop multimodal applications leveraging Mistral Medium 3.
- Adopt security and compliance best practices tailored for enterprise environments.
Course Delivery Format
- Engaging interactive lectures and discussions.
- Extensive exercises and practical activities.
- Hands-on implementation within a live-lab setting.
Customization Options
- For customized training sessions, please get in touch with us to make arrangements.
Mistral for Responsible AI: Privacy, Data Residency & Enterprise Controls
14 HoursMistral AI offers an open-source, enterprise-ready AI platform equipped with features designed to facilitate secure, compliant, and responsible AI deployment.
This instructor-led live training (available online or onsite) targets intermediate-level compliance leads, security architects, and legal/operations stakeholders who aim to implement responsible AI practices using Mistral through privacy, data residency, and enterprise control mechanisms.
Upon completion of this training, participants will be able to:
- Implement privacy-preserving techniques in Mistral deployments.
- Apply data residency strategies to meet regulatory requirements.
- Set up enterprise-grade controls such as RBAC, SSO, and audit logs.
- Evaluate vendor and deployment options for compliance alignment.
Format of the Course
- Interactive lecture and discussion.
- Compliance-focused case studies and exercises.
- Hands-on implementation of enterprise AI controls.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Multimodal Applications with Mistral Models (Vision, OCR, & Document Understanding)
14 HoursMistral models are open-source AI technologies that have expanded into multimodal workflows, supporting both language and vision tasks for enterprise and research applications.
This instructor-led, live training (available online or on-site) is designed for intermediate-level ML researchers, applied engineers, and product teams who aim to build multimodal applications with Mistral models, including OCR and document understanding pipelines.
By the end of this training, participants will be able to:
- Set up and configure Mistral models for multimodal tasks.
- Implement OCR workflows and integrate them with NLP pipelines.
- Design document understanding applications for enterprise use cases.
- Develop vision-text search and assistive UI functionalities.
Course Format
- Interactive lectures and discussions.
- Hands-on coding exercises.
- Live-lab implementation of multimodal pipelines.
Customization Options
- To request a customized training session for this course, please contact us to arrange.
