Compsia

Operating knowledge · Source-aware publishing

Evidence for making AI operational.

Evidence-led guides to enterprise AI adoption, AI automation, security, privacy, governance and production operation. Every article states its boundary, preserves its approved wording and separates operating guidance from unsupported customer claims.

Two connected clusters01

Publish the architecture, not a pile of keywords.

These clusters connect business automation with enterprise adoption, trust and production operation. Each article answers one real decision and links to the surrounding system.

01 · Mechanisms and economics

AI automation

Definitions, architecture choices, examples, cost and ROI frameworks for leaders who need a controlled production result rather than a tool demonstration.

02 · Trust through specificity

Enterprise AI

System-level guidance for security, privacy, infrastructure, GDPR and governance—bounded to exact data and action paths instead of blanket claims.

Launch library02
Enterprise AI9 min read

Enterprise AI agents: A guide to selection and implementation

Enterprise AI agents plan and perform business tasks using connected tools. Learn how to choose their scope, assign owners, and approve production use.
Enterprise AI8 min read

How to estimate AI development costs

Estimate AI development costs by separating build, production acceptance, and ongoing operation. Use a scope checklist to compare enterprise proposals.
AI automation9 min read

How to implement an automated business process

Build an automated business process with defined rules, appropriate AI use, accountable owners, acceptance tests, and a practical operating plan.
Enterprise AI8 min read

How to set workshop ground rules for an AI workshop

Set workshop ground rules for honest AI discussions about data, jobs, and errors, with a practical template, facilitator guidance, and decision criteria.
Enterprise AI8 min read

Implementation of artificial intelligence: A Practical Guide

Implement AI by defining a business result, assigning owners, testing data and action boundaries, and setting production acceptance and operating rules.
Enterprise AI8 min read

Generative AI development services: A buyer guide

Generative AI development services should cover design, integration, testing and operation. Use this guide to define scope, compare proposals and budget.
Enterprise AI8 min read

AI Training for Executives: A Workshop Planning Guide

Plan AI training for executives with a workshop owner map, preparation checklist, decision rules, and a practical way to choose who should participate.
Enterprise AI9 min read

How to choose AI integration services

Choose AI integration services with a framework for scope, ownership, implementation, production acceptance, costs, and provider evaluation.
AI automation8 min read

AI automation services: An Enterprise Buyer Guide

AI automation services help build and operate business workflows. Learn how to define scope, compare providers, budget, and approve production use.
Enterprise AI10 min read

AI Software Development Services: Enterprise Buyer Guide

A practical guide to selecting AI software development services, defining scope, governing risk, estimating costs, and operating systems.
Enterprise AI11 min read

How to Run an AI Workshop for Your Leadership Team

How to run an AI workshop for your leadership team: choose the decision first, bring the right owners and leave with an owned next step.
Enterprise AI9 min read

Artificial Intelligence Integration Services: A Production Guide

Learn how to scope, govern and operate artificial intelligence integration services around a clearly defined enterprise result.
Enterprise AI9 min read

UiPath Alternative for Enterprises That Need One Accountable System, Not a Platform License

Evaluating a UiPath alternative? See why the real choice is between licensing a platform and getting one accountable, operated production system.
Enterprise AI8 min read

What Is an AI Production System (And Why It's Not a Pilot or a Platform)

A precise definition of an AI production system: bounded scope, controls, and ongoing operation — and how it differs from a pilot or a licensed platform.
Enterprise AI9 min read

Why AI Pilot to Production Fails Without a Bounded System Definition

Most AI pilots stall not from bad tooling but missing scope. Learn the five elements a bounded production system needs to move past pilot.
Enterprise AI9 min read

AI Agent Orchestration Architecture: The Controls Most Frameworks Leave Out

Orchestration frameworks route tasks between agents. Production needs approval gates, prohibited actions, and fallback. Here's the architecture difference.
Enterprise AI8 min read

Enterprise AI Governance: What Actually Needs Approval, Monitoring, and Fallback

Enterprise AI governance made concrete: the approvals, prohibited behaviors, and fallback paths a single production system needs before release.
Child page under secure enterprise AI7 minute read

AI Production Security Checklist: Two Release Gates

Use two practical security gates to decide when an AI system may process real data and when it may run recurring, action-capable production work.
Action authority under the secure-enterprise-AI pillar7 minute read

AI Agent Write Access: A Safe Permission Model

Learn how to separate AI agent read, draft, and write authority with scoped tools, deterministic policy, authenticated approval, and replay-safe execution.
Data and retrieval security under secure enterprise AI7 minute read

RAG Access Control: Enforce Permissions at Retrieval

Design permission-aware RAG with caller identity, source authorization, filtered retrieval, evidence checks, safe caching, and production access tests.
Child page under private AI infrastructure and secure enterprise AI7 minute read

Private AI Security: Why Hosting Is Only One Control

Assess private AI security across identity, retrieval, applications, tools, releases, and operation before treating hosting ownership as protection.
Technical production operations under secure enterprise AI7 minute read

AI Environment Isolation: Lessons From a Production Incident

Learn how separate data, runtimes, credentials, releases, side effects, target assertions, backups, and tripwires protect AI production environments.
Commercial child page connecting enterprise trust content to Compsia's offer7 minute read

Secure Enterprise AI Solutions: What Buyers Should Compare

Compare secure enterprise AI solutions by business result, data, integrations, permissions, testing, evidence, operation, and total responsibility.
Procurement child under secure enterprise AI solutions7 minute read

25 AI Vendor Security Questions for Enterprise Buyers

Use 25 AI vendor security questions to assess data paths, providers, access, retrieval, model controls, actions, evidence, and production operation.
EU AI Act for enterprise adoption7 minute read

EU AI Act 2026: What Businesses Must Do Now

Understand the EU AI Act's current deadlines, classify one AI system, assign provider and deployer roles, and build an evidence-based action plan.
EU AI Act implementation6 minute read

EU AI Act Compliance Checklist for Enterprise Systems

Use a seven-stage EU AI Act compliance checklist covering scope, roles, classification, immediate duties, suppliers, release evidence, and monitoring.
EU AI Act classification6 minute read

EU AI Act High-Risk Systems: A Classification Guide

Learn how intended purpose, Article 6, Annex I, and Annex III determine high-risk AI classification, and why human approval is a control, not an exemption.
EU AI Act roles and procurement5 minute read

EU AI Act Provider vs Deployer: Assign the Right Role

Compare EU AI Act provider and deployer roles using intended purpose, branding, development, release control, operation, and Article 25 changes.
EU AI Act organizational readiness5 minute read

EU AI Act AI Literacy: A Practical Article 4 Plan

Build role-based EU AI Act literacy measures for users, approvers, system owners, and technical administrators using practical failure cases.
EU AI Act operational evidence5 minute read

AI System Inventory for EU AI Act Readiness

Build an AI system inventory covering purpose, roles, data, models, retrieval, actions, classification, evidence, versions, and review triggers.
EU AI Act classification5 minute read

EU AI Act Risk Classification: A Decision Tree

Classify an AI system through scope, prohibited practices, high-risk uses, Article 50 transparency, GPAI duties, roles, and review triggers.
EU AI Act and data governance5 minute read

EU AI Act vs GDPR: Two Reviews, One System Map

Compare the EU AI Act and GDPR across scope, roles, purpose, data, risk assessments, providers, logs, rights, and shared system evidence.
EU AI Act classification and use policy5 minute read

EU AI Act Prohibited Practices: An Article 5 Screen

Screen proposed AI uses against Article 5 using the practice, affected people, data, objective, effect, exceptions, and enforceable system limits.
EU AI Act transparency5 minute read

EU AI Act Article 50: Transparency Rules Explained

Apply Article 50 across direct AI interactions, machine-readable marking, deepfakes, public-interest text, human review, and accessible disclosure.
EU AI Act system controls5 minute read

EU AI Act Human Oversight: Design a Real Control

Design EU AI Act human oversight around identity, competence, context, authority, timing, evidence, automation bias, intervention, and safe stopping.
EU AI Act technical evidence5 minute read

EU AI Act Logging Requirements for Production Systems

Design AI Act logs across requests, sources, models, policy, approvals, execution, outcomes, retention, privacy, investigation, and recovery.
EU AI Act technical evidence5 minute read

EU AI Act Technical Documentation: Build the System File

Build EU AI Act technical documentation across purpose, design, data, performance, risk, controls, release evidence, operation, and change history.
EU AI Act data and retrieval5 minute read

RAG and the EU AI Act: Data, Access and Evidence

Assess RAG under the EU AI Act across classification, data roles, source scope, authorization, indexing, ranking, model context, provenance, and change.
EU AI Act and agentic systems5 minute read

EU AI Act and AI Agents: Classify Purpose, Control Action

Assess AI agents under the EU AI Act by intended purpose, role, tool authority, deterministic policy, human oversight, execution evidence, and change.
EU AI Act procurement5 minute read

25 EU AI Act Questions to Ask an AI Vendor

Ask AI vendors 25 questions about roles, classification, models, data, documentation, transparency, oversight, logs, incidents, changes, and exit.
EU AI Act AI value chain5 minute read

GPAI Code of Practice: What Enterprise Buyers Need

Understand the GPAI Code's scope, chapters, signatory evidence, provider questions, downstream limits, model-route records, and change triggers.
EU AI Act lifecycle and value chain5 minute read

EU AI Act Substantial Modification: A Change Review

Review AI system changes across purpose, people, models, data, authority, performance, branding, evidence, contracts, and provider responsibility.
AI automation8 minute read

What Is AI Automation? A Production Definition

AI automation explained for business leaders: what it is, how it differs from ordinary automation, when to use it and what production readiness requires.
AI automation8 minute read

AI Agents vs Workflows: Choose by Decision Freedom

Compare AI agents and workflows by autonomy, variability, testability, authority and production risk—and choose the smallest architecture that fits the result.
AI automation9 minute read

AI Automation Examples That Belong in Production

Five realistic AI automation examples with sources, controls, approval boundaries, fallback and measures—from document intake to account operations.
AI automation8 minute read

AI Automation ROI: A Baseline-to-Operation Framework

Calculate AI automation ROI without invented productivity claims: set a baseline, count full operating cost, measure accepted outcomes and account for risk.
AI automation8 minute read

AI Automation Costs: What a Production Budget Must Include

Understand AI automation costs across design, integration, data, acceptance, adoption, model usage, monitoring, support and controlled change.
Enterprise AI10 minute read

AI and GDPR Compliance: A System-by-System Framework

A system-level GDPR framework for AI: purpose, role, lawful basis, minimisation, transparency, rights, providers, security and accountability.
Enterprise AI9 minute read

AI Data Privacy: Map the Full Context Path

A production guide to AI data privacy across prompts, retrieval, model providers, tools, logs, outputs, human review, retention and deletion.
Enterprise AI10 minute read

AI Governance: From Policy to Production Decisions

An operational AI governance model for portfolio selection, system ownership, risk classification, acceptance, release evidence, monitoring and retirement.
Enterprise AI trust and production readiness8 minute read

Secure Enterprise AI: A Production System Framework

Learn how to assess secure enterprise AI across data, identities, retrieval, models, tools, actions, testing, releases, and ongoing operation.
Enterprise AI architecture and trust8 minute read

Private AI Infrastructure: Define the Right Boundary

Compare private AI infrastructure patterns across data, network, compute, models, tenancy, and geography, with a practical requirement framework.